recall rate

Context: Neonatal mass screening program for congenital hypothyroidism provides the best tool for prevention of its devastating effects on mental development. Despite the overall success of the screening programs in detecting congenital hypothyroidism and eliminating its sequelae and new developments made in the program design, high recall rate and false positive results impose a great challenge worldwide. Lower recall rate and false positive results may properly organize project expenses by reducing the unnecessary repeated laboratory tests, increase physicians and parents' assurance and cooperation, as well as reduce the psychological effects in families. Evidence Acquisition: In this review, we assessed the recall rate in different programs and its risk factors worldwide. Methods: Publications reporting the results of the CH screening program from 1997 to 2016 focusing on the recall rate have been searched. Results: Recall rates vary from 0.01% to 13.3% in different programs; this wide range may be due to different protocols of screening (use of T4 or TSH or both), different laboratory techniques, site of sample collection, recall cutoff, iodine status, human error, and even CH incidence as affected by social, cultural, and regional factors of the population. Conclusions: It is suggested to implement suitable interventions to reduce the contributing factors by improving the quality of laboratory tests, selecting conservative cut off points, control iodine deficiency, use of iodine free antiseptic during delivery, and use of more specific markers or molecular tests. Applying an age dependent criteria for thyrotropin levels can be helpful in regions with a varied time of discharge after delivery or for preterm babies.

This paper introduces a novel approach that incorporates two distinct activation functions-Exponential Linear Unit (ELU) and HardSwish-ELU-to enhance sign language recognition using the pre-trained YOLOv5 object recognition model. Various experiments were conducted on the ArSL21L dataset, a large-scale Arabic sign language dataset, to assess the proposed fusion of activation functions in terms of accuracy, precision, and recall. The combination of ELU and HardSwish enables better representation learning, allowing the model to capture intricate sign language gestures more accurately. The proposed model's effectiveness was further assessed using the OkkhorNama: BdSL dataset and ASLL (American Sign Language Letters) dataset, demonstrating significant improvements in recognition rates compared to the baseline YOLOv5 model with conventional activation functions. The proposed model achieved maximum levels of accuracy, recall, mAP 0.5, and mAP 0.5:0.95 at 98.2%, 98.5%, 99.1%, and 84.4%, respectively. Finally, the proposed model was tested in a real-time environment under various conditions, demonstrating its reliability and efficacy.

Context: Neonatal mass screening program for congenital hypothyroidism provides the best tool for prevention of its devastating effects on mental development. Despite the overall success of the screening programs in detecting congenital hypothyroidism and eliminating its sequelae and new developments made in the program design, high recall rate and false positive results impose a great challenge worldwide. Lower recall rate and false positive results may properly organize project expenses by reducing the unnecessary repeated laboratory tests, increase physicians and parents' assurance and cooperation, as well as reduce the psychological effects in families. Evidence Acquisition: In this review, we assessed the recall rate in different programs and its risk factors worldwide. Methods: Publications reporting the results of the CH screening program from 1997 to 2016 focusing on the recall rate have been searched. Results: Recall rates vary from 0.01% to 13.3% in different programs; this wide range may be due to different protocols of screening (use of T4 or TSH or both), different laboratory techniques, site of sample collection, recall cutoff, iodine status, human error, and even CH incidence as affected by social, cultural, and regional factors of the population. Conclusions: It is suggested to implement suitable interventions to reduce the contributing factors by improving the quality of laboratory tests, selecting conservative cut off points, control iodine deficiency, use of iodine free antiseptic during delivery, and use of more specific markers or molecular tests. Applying an age dependent criteria for thyrotropin levels can be helpful in regions with a varied time of discharge after delivery or for preterm babies.

A challenging task in Chinese collocation extraction is to improve both the precision and recall rate. Most lexical statistical methods including Xtract face the problem of unable to extract collocations with lower frequencies than a given threshold. This paper presents a method where HowNet is used to find synonyms using a similarity function. Based on such synonym information, we have successfully extracted synonymous collocations which normally cannot be extracted using the lexical statistical approach. We applied synonyms mapping to each headword to extract more synonymous word bi-grams. Our evaluation over 60MB tagged corpus shows that we can extract synonymous collocations that occur with very low frequency, sometimes even for collocations that occur only once in the training set. Comparing to a collocation extraction system based on Xtract, we have reached the precision rate of 43% on word bi-grams for a set of 9 headwords, almost 50% improvement from precision rate of 30% in...

Objectives: The aim of this study was to evaluate the clinical performance of a nano filled flowable and nano hybrid bulk fill resin composite in class I restorations. Methods and Materials: Twenty patients were selected for this in vivo study. Each patient received at least one pair of restorations, restored with nano hybrid bulk fill resin composite (IPS Empress direct [IED]) and nano hybrid Tetric N Ceram flowable composite [TNC]. Each restorative resin system was used with its respective adhesive system according to manufacturers’ instructions. A total of 40 class I restorations were placed by one operator.  Restorations were blindly evaluated by two examiners at baseline and 3, 6, and 12 months respectively using modified US Public Health Service Ryge criteria. The data obtained was statistically analyzed using Chi square test to compare the two restorative materials for each category. Results: At 3, 6 and 12, months, recall rate was 100%, 95% and 85%, respectively, with a rete...

Skin disinfection with povidine-iodine (PVP-I) is widely used in obstetrics. We evaluated the influence of PVP-I in mothers at delivery on the serum thyroid stimulating hormone concentrations of their infants at the time of screening for congenital hypothyroidism. The study covered 4745 infants who were either breast fed (3659, 77%) or bottle fed (1086, 23%); 3086 (65%) of them were born to mothers with no iodine overload (controls) and 1659 (35%) to mothers with iodine overload. Compared with the control group, the breast and bottle fed infants born to mothers with iodide overload had a shift of neonatal thyroid stimulating hormone concentration towards high values. The shift was maximal in the breast fed infants with a 25 to 30 fold increase in the recall rate at screening for congenital hypothyroidism (serum thyroid stimulating hormone >50 mU/l) while in the bottle fed infants, the recall rate was barely modified. In conclusion, the use of PVP-I in mothers at delivery induces a transient impairment of thyroid function in their infants, especially if breast fed. This situation is detrimental to screening for congenital hypothyroidism. Consequently PVP-I is not recommended in obstetrics. Skin disinfection with povidone-iodine (PVP-I) is programs. In: Burrow GN, Dussault JH, eds. Neonatal thyroid screening. New York: Raven Press, 1980:189-98. 12 Fyro K, Bodegard G. Four-year follow-up of psychological reactions to false positive screening tests for congenital hypothyroidism. Paediatr Scand 1987;76:107-14.

Objective: To compare self-referred screenees with respondents to invitation for main performance indicators of mammography screening. Setting: First round of an organised, population-based screening programme in six districts of northern Italy. The screening test was a two-view mammography. Eligible women aged 50-69 years were invited. Self-referred attendees were accepted if they were eligible for screening and had not yet been invited or had been invited >6 months before presentation. Age-speci c performance indicators were compared with the calculation of their ratio and 95% con dence intervals (CIs). Total ratios were agestandardised. In situ carcinomas were excluded. The eligible population was 183 542 women. There were 112 188 respondents to invitation and 20 280 self-referred attendees. Self-referral rate was inversely related to age. Performance indicators were as follows: recall rate, 5.6% for self-referred attendees vs 5.5% for respondents (ratio 1.02, 95% CI 0.96 to 1.08); total aspiration cytology rate, 37.3% vs 28.3% (1.37, 1.24 to 1.51); biopsy rate, 17.0 vs 12.6 ´1000 (1.51, 1.35 to 1.67); total detection rate, 10.7 vs 7.5 ´1000 (1.70, 1.48 to 1.94); detection rate of pT1 carcinoma, 7.0 vs 6.1 ´1000 (1.35, 1.14 to 1.59); detection rate of pT2-4 carcinoma, 3.5 vs 1.2 ´1000 (3.51, 2.75 to 4.43); false-positive rate, 4.5% vs 4.7% (0.93, 0.87 to 0.99); positive predictive value (PPV) of mammography, 19.1% vs 13.5% (1.59, 1.39 to 1.82); PPV of biopsy, 63.7% vs 60.6% (1.13, 0.98 to 1.29); detected:expected ratio, 5.02 vs 3.37 (1.49, 1.28 to 1.74). All differences were more pronounced among or restricted to women aged 50-54 years. Self-referred screenees were similar to respondents to invitation in main indicators of screening feasibility such as recall rate and PPV of biopsy, while showing important increases in detection rates and detected:expected ratios, especially among women aged 50-54 years.

The expansion of aquaculture necessitates innovative disease detection methods to ensure sustainable production. Fish diseases caused by bacteria, viruses, fungi, and parasites result in significant economic losses and threaten food security. Traditional detection methods are labor-intensive and time-consuming, emphasizing the need for automated approaches. This study investigates the application of convolutional neural networks (CNNs) for classifying freshwater fish diseases. Such CNNs offer an efficient and automated solution for fish disease detection, reducing the burden on aquatic health experts and enabling timely interventions to mitigate economic losses. A dataset of 2444 images was used across seven classes-bacterial red disease, bacterial Aeromoniasis disease, bacterial gill disease, fungal disease, parasitic diseases, white tail disease, and healthy fish. The CNNs model incorporates convolutional layers for feature extraction, max-pooling for down-sampling, dense layers for classification, and dropout for regularization. Categorical cross-entropy loss and the Adam optimizer were used over 50 epochs, with continuous training and validation performance monitoring. The results indicated that the model achieved an accuracy of 99.71% and a test loss of 0.0119. This study highlights the transformative potential of artificial intelligence in aquaculture for enhancing food security.

To evaluate the effect of the introduction of digital mammography on the recall rate, detection rate, false-positive rate, and rates of invasive procedures in a cohort of women from four population-based breast cancer screening programs in Spain. Methods: The study was approved by the ethics committee; informed consent was not required. A total of 242 838 mammograms (171 191 screen fi lm [screen-fi lm mammography group] and 71 647 digital [digital mammography group]) obtained in 103 613 women aged 45 -69 years were included. False-positive results for any additional procedure and for invasive procedures, the breast cancer rate, and the positive predictive value in each group were compared by using Pearson x 2 test. The effect of the mammographic technology used (screen-fi lm or digital) on the false-positive results and cancer detection risk was evaluated with multivariate logistic regression models, adjusted according to women's and the screening program's characteristics and time trends. The false-positive rate was higher for screen-fi lm than for digital mammography (7.6% and 5.7%, respectively; P , .001). False-positive results after an invasive procedure were signifi cantly higher for screen-fi lm than for digital mammography (1.9% and 0.7%, respectively; P , .001). No signifi cant differences were observed in the overall cancer detection rate between the two groups (0.45% and 0.43% in the screen-fi lm and digital mammography groups, respectively; P = .59). The adjusted risk of a falsepositive result was higher for screen-fi lm than for digital mammography (odds ratio = 1.32). The adjusted risk was also lower for the digital mammography group when time trends were taken into account. The lower false-positive risk with use of digital mammography should be taken into account when balancing the risks and benefi ts of breast cancer screening.

The introduction of flowable composites provide expanded options for restorative dentistry. There is a growing trend among practitioners to use bulk-fill resin based composite materials because of their more simplified procedures. The main advancement of bulk-fill composite materials, namely increased depth of cure, which probably results from higher translucency, and low polymerization shrinkage stress are related to modifications in the filler content and/or organic matrix with the help of advanced technology. This article has enlighten different aspects of flowable bulkfill composite resin materials.

Background:The proportion of newborns recalled during neonatal screening programs for congenital hypothyroidism (CH) varies substantially by country and may be higher in settings where povodine iodine (PVP-I) is used during delivery. We assessed this hypothesis by substituting PVP-I for chlorhexidine (CHL) and evaluated the reduction in the recall rate of the Irainian newborn screening program.Methods:This study investigated 2282 neonates of mothers admitted to a local hospital for delivery between December 2012 and October 2013. We measured thyorid stimulating hormone (TSH) levels in heel-prick blood specimens of infants, aged between 3 and 5 days, born to mothers who received PVP-I (phase I) and those who received CHL after withdrawal of PVP-I from obstetric procedures (phase II). Then we compared the median TSH levels and the recall rate based on a TSH level ≥5 mU/L.Results:Of 2282 cases, 1094 infants were born to mothers exposed to PVP-I during phase I (PVP-I group) and 1188 one...

The named-entity phrases in free text represent a formidable challenge to text analysis. Translating a named-entity is important for the task of Cross Language Information Retrieval and Question Answering. However, both tasks are not easy to handle because named-entities found in free text are often not listed in a monolingual or bilingual dictionary. Although it is possible to identify and translate named-entities on the fly without a list of proper names and transliterations, an extensive list certainly will ensure the high accuracy rate of text analysis. We use a list of proper names and transliterations to train a Machine Transliteration Model. With the model it is possible to extract proper names and their transliterations in a bilingual corpus with high average precision and recall rates.

This study evaluated the one-year clinical performance of a one-step, self-etch adhesive (Optibond All-in-One, Kerr, CA, USA) combined with a composite (Herculite XRV Ultra, Kerr Hawe, CA, USA) to restore NCCLs with or without prior acid etching. Restorations performed by the same practitioner were evaluated at baseline and after 3, 6, and 12 months using modified USPHS criteria. At 6 months, the recall rate was 100%. The retention rate was 84.2% for restorations with prior acid etching, but statistically significant differences were observed between baseline and 6 months. Without acid etching, the retention rate was 77%, and no statistically significant difference was noted between 3 and 6 months. Marginal integrity (93.7% with and 87.7% without acid etching) and discoloration (95.3% with and 92.9% without acid etching) were scored as Alpha or Bravo, with better results after acid etching. After one year, the recall rate was 58.06%. Loss of pulp vitality, postoperative sensitivity,...

Se concluye la conveniencia de revisar el modelo de tamización neonatal actual, considerando la centralización, el mejoramiento en la asistencia a la nueva cita para confirmación y la cobertura, y la implementación de la tamización neonatal expandida por espectrometría de masas.

Automatic plagiarism detection considering a reference corpus compares a suspicious text to a set of original documents in order to relate the plagiarised fragments to their potential source. Publications on this task often assume that the search space (the set of reference documents) is a narrow set where any search strategy will produce a good output in a short time. However, this is not always true. Reference corpora are often composed of a big set of original documents where a simple exhaustive search strategy becomes practically impossible. Before carrying out an exhaustive search, it is necessary to reduce the search space, represented by the documents in the reference corpus, as much as possible. Our experiments with the METER corpus show that a previous search space reduction stage, based on the Kullback-Leibler symmetric distance, reduces the search process time dramatically. Additionally, it improves the Precision and Recall obtained by a search strategy based on the exhaustive comparison of word n-grams.

The development of computer vision technology is growing very fast and penetrating all sectors, including fisheries. This research focuses on detecting and counting catfish fry. This research aims to apply deep learning in detecting catfish fry objects and counting accurately so as to help farmers and buyers reduce the risk of loss. The detection system in this research uses digital image processing techniques as a way to obtain information from the detection object. The research method uses YOLO Object Detection which has a very fast ability to identify objects. The object detected is a catfish puppy object that is given a bounding box and the detection label displays the class name and precision value. The dataset amounted to 321 images of catfish puppies from internet and photography sources that were trained to produce a new digital image model. The number of split training, validation and testing datasets is worth 831 annotation images, 83 validation images and 83 images for the testing process. The value of the training model mAP 50.39 %, Precision 61.17 % and Recall 58 % Detection test results based on the YOLO method obtained an accuracy rate of 65.7%. The avg loss value in the final model built with YOLO is 4.6%. Based on the results of tests carried out with the number of objects 50 to 500 tail size 2-8 cm using video, objects in the image are successfully recognized with an accuracy of 63% to 70%. Calculations using the YOLO algorithm show quite good results.

SummaryThis report outlines the status of neonatal screening in Europe in 2004. Out of the 45 member states of the Council of Europe plus the regions Scotland and Wales (in total 47 ‘countries’), no data at all were available from 3 (Albania, Azerbaijan and Georgia). From the other 44, varying amounts of data were received. Apart from Armenia, Finland and Malta, all countries have a national programme for phenylketonuria (PKU), although in some countries those programmes do not yet have 100% coverage. Moldova and Ukraine have no national programme for congenital hypothyroidism (CH), the other countries do. Twelve countries screen for congenital adrenal hyperplasia (CAH), 6 for cystic fibrosis (CF) and 7 for galactosaemia (GAL), 6 for biotinidase deficiency (BD) and 4 for medium‐chain acyl‐CoA dehydrogenase deficiency (MCAD). Some countries have pilot programmes for certain conditions or different programmes per screening laboratory. The prevalences for PKU vary from 1:3000 to 1:30 0...

The number of patients that return for recall appointments has great importance to validate endodontic treatment outcomes. The purpose of this review was to investigate the rate of return on recall and the main factors that influence this rate of return. A literature review was performed in the PubMed database for the years from 1978 to 2017, using the following keywords: recall rate, endodontic treatment, endodontic retreatment, apical surgery. The inclusion criteria were: prospective studies in English, and in vivo research with humans, which included patient return rates. A total of 35 studies that fulfilled the established criteria were selected. The percentage of patients who returned on recall was 56%. More female patients (60%) attended the recall appointments than male (40%). The three main reasons for not returning were: patients did not observe the follow-up appointment (490), not returning due to a lack of interest (99) and   changing their address (222). The age of the p...

This study evaluated the one-year clinical performance of a one-step, self-etch adhesive (Optibond All-in-One, Kerr, CA, USA) combined with a composite (Herculite XRV Ultra, Kerr Hawe, CA, USA) to restore NCCLs with or without prior acid etching. Restorations performed by the same practitioner were evaluated at baseline and after 3, 6, and 12 months using modified USPHS criteria. At 6 months, the recall rate was 100%. The retention rate was 84.2% for restorations with prior acid etching, but statistically significant differences were observed between baseline and 6 months. Without acid etching, the retention rate was 77%, and no statistically significant difference was noted between 3 and 6 months. Marginal integrity (93.7% with and 87.7% without acid etching) and discoloration (95.3% with and 92.9% without acid etching) were scored as Alpha or Bravo, with better results after acid etching. After one year, the recall rate was 58.06%. Loss of pulp vitality, postoperative sensitivity,...

Closed-circuit television (CCTV) surveillance systems have been installed in public locations to search for missingchildren and fight crime. The Penang City Council has deployed a face recognition CCTV monitoring system. As a result, this research aims to identify children who were in the wrong area or at the wrong time and then notify authorities such as police and parents. According to child detection research, the average child loss rate is more significant due to lacking child detection features. Existing research employs machine learning and deep learning across several platforms, yielding inaccurate accuracy findings. Using the YOLOv5 algorithm, this study will categorize images based on children's detection in restricted locations. Coco, Coco128, and Pascal VOC were chosen because they are the standard datasets of YOLOv5 and the public dataset INRIA Person. Annotations and augmentation techniques are employed in the pre-processing phase to acquire labeling in text file fo...

With computer vision's growing potential, many companies have spent on object detection to interpret and analyze data primarily derived from visual sources for a wide range of applications, such as medical image classification, automated vehicle object recognition, face recognition for security reasons, and child detection in surveillance systems. Most research in the field of child detection involves prediction models [1], head and body ratio calculation [2], age group classification [3], and child versus adult classifier [4]. This distinction between children and adults improves social security since it makes it simpler to recognize criminals based on identifiable physical features. Several studies on the distinction among children and adults were presented. These investigations only apply to face characteristics or portions of the body and employed cameras with a near range of 20 to 50 cm [5]. Previous research has revealed why

Background: This study aimed to systematically review and to meta-analyse the accuracy of digital breast tomosynthesis (DBT) versus digital mammography (DM) in women with mammographically dense breasts in screening and diagnosis. Methods: Two independent reviewers identified screening or diagnostic studies reporting at least one of four outcomes (cancer detection rate-CDR, recall rate, sensitivity and specificity) for DBT and DM in women with mammographically dense breasts. Study quality was assessed using QUADAS-2. Meta-analysis of CDR and recall rate used a random effects model. Summary ROC curve summarized sensitivity and specificity. Results: Sixteen studies were included (five diagnostic; eleven screening). In diagnosis, DBT increased sensitivity (84%-90%) versus DM alone (69%-86%) but not specificity. DBT improved CDR versus DM alone (RR: 1.16, 95% CI 1. 02-1.31). In screening, DBT + DM increased CDR versus DM alone (RR: 1.33, 95% CI 1.20-1.47 for retrospective studies; RR: 1.52, 95% CI 1.08-2.11 for prospective studies). Recall rate was significantly reduced by DBT + DM in retrospective studies (RR: 0.72, 95% CI 0.64-0.80) but not in two prospective studies (RR: 1.12, 95% CI 0.76-1.63). In women with mammographically dense breasts, DBT+/-DM increased CDR significantly (versus DM) in screening and diagnosis. In diagnosis, DBT+/-DM increased sensitivity but not specificity. The effect of DBT + DM on recall rate in screening dense breasts varied between studies.

Objectives: The aim of this study was to evaluate the clinical performance of a nano filled flowable and nano hybrid bulk fill resin composite in class I restorations. Methods and Materials: Twenty patients were selected for this in vivo study. Each patient received at least one pair of restorations, restored with nano hybrid bulk fill resin composite (IPS Empress direct [IED]) and nano hybrid Tetric N Ceram flowable composite [TNC]. Each restorative resin system was used with its respective adhesive system according to manufacturers’ instructions. A total of 40 class I restorations were placed by one operator.  Restorations were blindly evaluated by two examiners at baseline and 3, 6, and 12 months respectively using modified US Public Health Service Ryge criteria. The data obtained was statistically analyzed using Chi square test to compare the two restorative materials for each category. Results: At 3, 6 and 12, months, recall rate was 100%, 95% and 85%, respectively, with a rete...

Websites can increase their security and prevent harmful Internet attacks by providing CAPTCHA verification for determining whether end-user is a human or a robot. Text-based CAPTCHA is the most common and designed to be easily recognized by humans and difficult to identify by machines or robots. However, with the dramatic advancements in deep learning, it becomes much easier to build convolutional neural network (CNN) models that can efficiently recognize text-based CAPTCHAs. In this study, we introduce an efficient CNN model that uses attached binary images to recognize CAPTCHAs. By making a specific number of copies of the input CAPTCHA image equal to the number of characters in that input CAPTCHA image and attaching distinct binary images to each copy, we build a new CNN model that can recognize CAPTCHAs effectively. The model has a simple structure and small storage size and does not require the segmentation of CAPTCHAs into individual characters. After training and testing the...

Background: The aim of this study was to compare after 24 months the clinical performance of cervical restorations placed with the use of an etch-and-rinse and an all-in-one adhesive. Methods: Twenty-four patients with at least one pair of non-carious cervical lesions participated in this study. One hundred and twenty-three cervical lesions were restored (62 etch-and-rinse adhesive, Solobond M; 61 all-in-one adhesive, Futurabond NR). A nanohybrid resin composite, Grandio, was used as the restorative material. Restorations were evaluated according to modified USPHS criteria by two independent examiners. The survival rates of the restorations were calculated by the Kaplan-Meier estimator and log-rank test. The restorations in each category were compared using the Pearson chi-square test, while the performance of restorations at the baseline and at each recall time was evaluated by McNemar's test (p < 0.05). Results: The recall rate of patients was 100%. The retention rates were 82% and 75% at 6 months and 77% and 62% at 12 months for Solobond M and Futurabond NR, respectively. At the 24-month recall, the retention rate was 69% for Solobond M and 49% for Futurabond NR, and this difference was statistically significant (p < 0.05). No statistically significant difference was found for colour match, marginal staining, or marginal adaptation between the adhesives (p > 0.05). None of the restorations had secondary caries, loss of anatomical form, or surface texture changes. Conclusions: Cervical restorations placed with an etch-and-rinse adhesive showed higher retention than an all-in-one adhesive.

Engineering drawings contain many curves that intersect at a complex junction. Detection of these junctions is vital for correct recognition of line drawings. In this paper we study the detection of junctions in document images. A threestage junction detection is proposed to detect junctions in document images. The first stage works at the pixel level. Any pixel with more than two neighbors is labeled as low-level-junction. The second stage works at connected component level. All low-level-junctions adjacent to other low-level-junctions are merged into mid-level-junctions. The third stage combines mid-level-junction at a distance less than a threshold into a high-level-junction. Experimental results on real scanned images of mechanical engineering drawings show a precision rate of 82.38% and a recall rate of 97.29%.

 Since 2001 dried blood spots from newborns have been screened with a time-resolved fluoroimmunoassay method (DELFIA) for 17-OHP determination.  Over the years, the cut-off levels of 17OHP have been adjusted according to gestational age  Since 2017, samples resulted above the cut-off have been immediately analyzed by LC-MS/MS in order to differentiate affected patients from false positive newborns.

 Since 2001 dried blood spots from newborns have been screened with a time-resolved fluoroimmunoassay method (DELFIA) for 17-OHP determination.  Over the years, the cut-off levels of 17OHP have been adjusted according to gestational age  Since 2017, samples resulted above the cut-off have been immediately analyzed by LC-MS/MS in order to differentiate affected patients from false positive newborns.

E-texts have many advantages over their paper counterparts, especially when they are reflowable and available as open educational resources (OERs). Unfortunately, research suggests that etexts are, on the whole, less memorable than ptexts, in part due to their relative lack of visual navigational landmarks that help to anchor recall. The Landmarks project team is, therefore, building an application that inserts computer-generated artificial imperfections-abstract or representational landmarks-into the display of etexts, that remain consistently associated with text passages even when documents are reflowed or reformatted. We hypothesize that it may consequently be easier to recall the associated contents. The application is designed to provide the means to present modified open texts using a range of generated landmarks and variations on them, and to test recall of the content. In this initial pilot study, results of tests for readers receiving different landmarks will be compared, with the intent of identifying promising approaches to use for future studies.

This study evaluated the one-year clinical performance of a one-step, self-etch adhesive (Optibond All-in-One, Kerr, CA, USA) combined with a composite (Herculite XRV Ultra, Kerr Hawe, CA, USA) to restore NCCLs with or without prior acid etching. Restorations performed by the same practitioner were evaluated at baseline and after 3, 6, and 12 months using modified USPHS criteria. At 6 months, the recall rate was 100%. The retention rate was 84.2% for restorations with prior acid etching, but statistically significant differences were observed between baseline and 6 months. Without acid etching, the retention rate was 77%, and no statistically significant difference was noted between 3 and 6 months. Marginal integrity (93.7% with and 87.7% without acid etching) and discoloration (95.3% with and 92.9% without acid etching) were scored as Alpha or Bravo, with better results after acid etching. After one year, the recall rate was 58.06%. Loss of pulp vitality, postoperative sensitivity,...

Visual and infrared cameras have complementary properties and using them together may increase the performance of object detection applications. Although the fusion of visual and infrared information results in a better recall rate than using only one of those domains, there is always a decrease in the precision rate whereas the infrared domain on its own always has higher precision. Thus, the fusion of these domains is meaningful only for a better recall rate, which means that more foreground pixels are detected correctly. This study presents a new computationally more efficient and simpler method for extracting the complementary information from both domains and fusing them to obtain better recall rates than those previously achieved. The method has been tested using a well-known database and a database created for the study and compared with earlier fusion methods.

Visual and infrared cameras have complementary properties and using them together may increase the performance of object detection applications. Although the fusion of visual and infrared information results in a better recall rate than using only one of those domains, there is always a decrease in the precision rate whereas the infrared domain on its own always has higher precision. Thus, the fusion of these domains is meaningful only for a better recall rate, which means that more foreground pixels are detected correctly. This study presents a new computationally more efficient and simpler method for extracting the complementary information from both domains and fusing them to obtain better recall rates than those previously achieved. The method has been tested using a well-known database and a database created for the study and compared with earlier fusion methods.

Reliability and lifetime of specific electronics boards depends on the quality of manufacturing process. Especially soldering splashes in some areas of PCB (printed circuit board) can cause change of selected electrical parameters. Nowadays, the manual inspection is massively replaced by specialized visual systems checking the presence of different defects. The research carried out in this paper can be considered as industrial (industry requested) application of machine learning in automated object detection. Object of interest—solder splash—is characterized by its small area and similar properties (texture, color) as its surroundings. The aim of our research was to apply state-of-the art algorithms based on deep neural networks for detection such objects in relatively complex electronic board. The research compared seven different object detection models based on you-look-only-once (YOLO) and faster region based convolutional neural network architectures. Results show that our cust...

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The proposed LDDNet was developed using additional layers of 2D global average pooling, dense and dropout layers, and batch normalization to the base DenseNet201 model. There are 1024 Relu-activated dense layers and 256 dense layers using the sigmoid activation method. The hyper-parameters of the model, including the learning rate, batch size, epochs, and dropout rate, were tuned for the model. Next, three datasets of lung diseases were formed from separate open-access sources. One was a CT scan dataset containing 1043 images. Two X-ray datasets comprising images of COVID-19-affected lungs, pneumonia-affected lungs, and healthy lungs exist, with one being an imbalanced dataset with 5935 images and the other being a balanced dataset with 5002 im...

With computer vision's growing potential, many companies have spent on object detection to interpret and analyze data primarily derived from visual sources for a wide range of applications, such as medical image classification, automated vehicle object recognition, face recognition for security reasons, and child detection in surveillance systems. Most research in the field of child detection involves prediction models [1], head and body ratio calculation [2], age group classification [3], and child versus adult classifier [4]. This distinction between children and adults improves social security since it makes it simpler to recognize criminals based on identifiable physical features. Several studies on the distinction among children and adults were presented. These investigations only apply to face characteristics or portions of the body and employed cameras with a near range of 20 to 50 cm [5]. Previous research has revealed why

The aim of the current study was to present early performance indicators of a breast cancer screening program in Greece. Methods Between March 2004 and July 2009, 9621 women aged between 40 and 69 years were recruited into programme on a voluntary basis. The participating women were residents of two adjacent administrative regions of Greece. Several performance indicators were calculated for the first and subsequent screen, separately. Results A total of 9621 mammograms were 1st screens and 4462 were subsequent screens. The attendance rate was almost 1.5%. The technical repeat rate was 1.7%. On the 1st screen, the recall rate was 11.4%, while the recall rate of the subsequent screens was 5.5%. The vast majority of detected cancers were invasive and only the 1/7 of cancers was identified as DCIS. As concerns tumour size of invasive cancers, the 1.9% and 16.7% was unknown, in the first and subsequent screen, respectively. Moreover, 38.5% and 44.4% of cancers detected in the 1st and subsequent screen, respectively, were less than 15 mm in diameter. Almost 1/5 of diagnosed cancers were interval cancers. Conclusions This breast cancer screening programme is the first one in Greece and the attendance rate is extremely low. Taking into account that an organised screening programme may benefit women with a reduction in breast cancer mortality, there is an urgent need to develop a national-based screening programme, to increase participation and to improve the information system used to monitor programme performance.

Newborn screening for congenital hypothyroidism (CH) was implemented in Hospital UKM in December 2004 using cord blood sample. From the audit over a period of 25 months, a total of 13,875 newborn babies were screened with a coverage of 98.8%. From this cohort, the mean recall rate was 0.32%; unfortunately the mean percentage of recalled babies that came for retesting was only 79.5%. In addition, the mean sample rejection rate was high, i.e. 2.2%. Two babies were diagnosed to have CH. These findings implied that whilst the coverage of screening was good, there is a need for regular surveillance of performance of both clinical and laboratory personnel. In addition, a more concerted effort should be carried out to promote community awareness of such a programme.

The aim of this study was to determine the recall rate of screening ultrasound with automated breast volumetric scanning (ABVS) in women with dense breasts (BI-RADS density classification 3 or 4 on mammogram). Materials and Methods: In this retrospective cohort study, at the end of the "first quarter" (August-October 2013) of use, our practice database was searched for all ABVS examinations performed and specifically, the positive examinations (defined as abnormal/BI-RADS 0) for which patients were recalled for additional imaging evaluation with handheld ultrasound (HHUS); the latter group was reviewed with respect to final BI-RADS and pathology if relevant. Results: During the 3-month study time period, 558 ABVS studies were performed: 453 (81%) were initially BI-RADS 1 or 2 and 105 (19%) were BI-RADS 0-incomplete and recalled, corresponding with an overall recall rate of 19%; specifically, the recall rate trended down from 24.7% in August to 12.6% in October. To date, 98 of the 105 recalled women have returned for HHUS, with the resultant final BI-RADS as follows: 25/98=25% BI-RADS 1, 46/98=47% BI-RADS 2, 13/98=13% BI-RADS 3, 14/98=15% BI-RADS 4, and 0/98=0% BI-RADS 5. All biopsies performed to date of the ABVS-detected BI-RADS 4 lesions have yielded benign results, with the most common pathology being fibroadenoma. Conclusion: The recall rate of screening ABVS in women with dense breasts at our institution was under 20% overall during its first quarter of use, and trended down from nearly 25% in the first month to under 13% in the third. The clinical implication is that ABVS does have a learning curve, but that is a potentially feasible way to meet the increasing demands for screening ultrasound in women with dense breasts.

To evaluate the effect of the introduction of digital mammography on the recall rate, detection rate, false-positive rate, and rates of invasive procedures in a cohort of women from four population-based breast cancer screening programs in Spain. Materials and Methods: The study was approved by the ethics committee; informed consent was not required. A total of 242 838 mammograms (171 191 screen fi lm [screen-fi lm mammography group] and 71 647 digital [digital mammography group]) obtained in 103 613 women aged 45-69 years were included. False-positive results for any additional procedure and for invasive procedures, the breast cancer rate, and the positive predictive value in each group were compared by using Pearson x 2 test. The effect of the mammographic technology used (screen-fi lm or digital) on the false-positive results and cancer detection risk was evaluated with multivariate logistic regression models, adjusted according to women's and the screening program's characteristics and time trends. Results: The false-positive rate was higher for screen-fi lm than for digital mammography (7.6% and 5.7%, respectively; P , .001). False-positive results after an invasive procedure were signifi cantly higher for screen-fi lm than for digital mammography (1.9% and 0.7%, respectively; P , .001). No signifi cant differences were observed in the overall cancer detection rate between the two groups (0.45% and 0.43% in the screen-fi lm and digital mammography groups, respectively; P = .59). The adjusted risk of a falsepositive result was higher for screen-fi lm than for digital mammography (odds ratio = 1.32). The adjusted risk was also lower for the digital mammography group when time trends were taken into account. Conclusion: The lower false-positive risk with use of digital mammography should be taken into account when balancing the risks and benefi ts of breast cancer screening.

To examine recall rates from screening mammography and the mammographic findings that caused recall in women who underwent digital breast tomosynthesis with conventional mammography (referred to as two-dimensional [2D] with three-dimensional [3D] imaging [2D+3D]) and in women who underwent conventional mammography alone (referred to as 2D). Materials and Methods: This was an institutional review board-approved, HIPAAcompliant study with waivers of informed consent. A retrospective review of 2D+3D and 2D screening mammograms from August 1, 2011, to December 31, 2012, was performed. Recall rates and abnormalities that caused recall were compared by controlling for differences in patient age, breast density, and risk factors. Cancer detection rate was assessed from this time period and from 1 year before the introduction of tomosynthesis for a historic control. Results: This study included 17 955 screening mammograms; of the total, there were 8591 (47.8%) 2D+3D screening examinations and 9364 (52.2%) 2D examinations. The recall rate was 7.8% (671 of 8592) for 2D+3D and 12.3% (1154 of 9364) for 2D (P , .0001); the rate of recall was 36.6% lower in the 2D+3D group than in the 2D group. Recall rates for the 2D+3D group were significantly lower for patients with asymmetries, (2D+3D vs 2D, 3.1% [267 of 8591] vs 7.4% [689 of 9364], respectively; P , .0001) and calcifications (2D+3D vs 2D, 2.4% [205 of 8591] vs 3.2% [297 of 9364], respectively; P = .0014). For patients with masses and architectural distortion, the difference in recall rates was not significant (masses: 2D+3D vs 2D, 2.5% [215 of 8591] vs 2.5% [237 of 9364], respectively; P = .90; architectural distortion: 2D+3D vs 2D, 0.68% [58 of 8591] vs 0.69% [65 of 9364]; P = .88). Cancer detection was highest in the 2D+3D group at 5.9 cancers per 1000 examinations, with 5.7 cancers per 1000 examinations in the concurrent 2D group, and 4.4 cancers per 1000 examinations in the historic control. Conclusion: Use of tomosynthesis (2D+3D) compared with conventional mammography (2D) is associated with a lower recall rate of screening mammography, most often for asymmetries.

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The proposed LDDNet was developed using additional layers of 2D global average pooling, dense and dropout layers, and batch normalization to the base DenseNet201 model. There are 1024 Relu-activated dense layers and 256 dense layers using the sigmoid activation method. The hyper-parameters of the model, including the learning rate, batch size, epochs, and dropout rate, were tuned for the model. Next, three datasets of lung diseases were formed from separate open-access sources. One was a CT scan dataset containing 1043 images. Two X-ray datasets comprising images of COVID-19-affected lungs, pneumonia-affected lungs, and healthy lungs exist, with one being an imbalanced dataset with 5935 images and the other being a balanced dataset with 5002 im...

A patent always contains some images along with the text. Many text based systems have been developed to search the patent database. In this paper, we describe PATSEEK that is an image based search system for US patent database. The objective is to let the user check the similarity of his query image with the images that exist in US

In the digital forensics process based on Uygur language information, stem, affix, synonym mark and other characteristics are added on the featuresbased English and Chinese chunks and according to relevant characteristics of Uygur language. In terms of performance evaluation indexes in this paper, accuracy rate, recall rate and F value are adopted. The test indicates that the scale of Uyghur chunks database has great effects on the model performance.

Freshwater fish is considered a poor man's protein supplement as they are easily available in lakes, rivers, natural ponds, paddy fields, beels, and fisheries. There are various freshwater fish species that resemble each other, making it difficult to classify them by their external appearance. Manual fish species identification always needs expertise and so, is erroneous. Recently, computer vision along with deep learning plays a significant role in underwater species classification research where the number of species under investigation is always limited to a maximum of eight (8). In this article, we choose deep-learning architectures, AlexNet and Resnet-50, to classify 20 indigenous freshwater fish species from the NorthEastern parts of India. The two models are fine-tuned for training and validation of the collected fish data. The performance of these networks is evaluated based on overall accuracy, precision, and recall rate. This paper reports the best overall classification accuracy, precision, and recall rate of 100% at a learning rate of 0.001 by the Resnet-50 model on our own dataset and benchmark Fish-Pak dataset. Comprehensive empirical analysis has proved that with an increasing Weight and Bias learning rate, the validation loss incurred by the classifier also increases.

EUSOBI and 30 national breast radiology bodies support mammography for population-based screening, demonstrated to reduce breast cancer (BC) mortality and treatment impact. According to the International Agency for Research on Cancer, the reduction in mortality is 40 % for

Objective: To analyse trends in the use of diagnostic test in breast cancer screening programs in Spain. Materials and methods: Retrospective study of 542,695 women who had undergone at least one screening mammogram in any of the screening centres of three administrative regions in Spain, between 1996 and 2011. Process measures were: overall recall rate, overall invasive test rate, and rates of each type of invasive test (fine-needle aspiration biopsy, core-needle biopsy and surgical biopsy). As results measures were included detection of benign lesions rate, ductal in situ cancer rate and invasive cancer rate. Adjusted by age rates were estimated year by year for each measure and, also, the annual percent of change and its corresponding joint points. Results: Core-needle biopsy rates decreased between 1996 and 1999 and changed trends in 1999-2011 with an increase of 4.9% per year. Overall recall rate declined by 4.6% from 1999 to 2004, invasive test rate declined between 1996 and 2004 by 24.3%. Fine-needle aspiration biopsy rate changes were: a 22.4% declined per year (1996-1998), and 13.5% declined per year (1998-2005). Benign lesions rate decreased from 1996 to 2011, 21.4% per year (1996-2001) and 6.0% (2001-2011). Ductal carcinoma in situ and invasive cancer had no-statistically significant changes.

Text detection in natural scene images for content analysis is an interesting task. The research community has seen some great developments for English/Mandarin text detection. However, Urdu text extraction in natural scene images is a task not well addressed. In this work, firstly, a new dataset is introduced for Urdu text in natural scene images. The dataset comprises of 500 standalone images acquired from real scenes. Secondly, the channel enhanced Maximally Stable Extremal Region (MSER) method is applied to extract Urdu text regions as candidates in an image. Two-stage filtering mechanism is applied to eliminate non-candidate regions. In the first stage, text and noise are classified based on their geometric properties. In the second stage, a support vector machine classifier is trained to discard non-text candidate regions. After this, text candidate regions are linked using centroid-based vertical and horizontal distances. Text lines are further analyzed by a different classif...