Papers by Mattakoyya Aharonu
Traitement du signal/TS. Traitement du signal, Apr 30, 2024
Lung cancer, recognized as one of the most lethal malignancies globally, manifests predominantly ... more Lung cancer, recognized as one of the most lethal malignancies globally, manifests predominantly as lung adenocarcinoma (LUAD) within the broader classification of nonsmall cell lung cancer (NSCLC). The imperative for accurate and prompt diagnosis to facilitate efficacious treatment underscores the significance of advancements in diagnostic methodologies. This study introduces a convolutional neural network (CNN) framework tailored for the interpretation of bioinformatics datasets, specifically focusing on the classification of lung adenocarcinoma. Emphasizing the integration of gene-based biomarker informatics, this approach endeavors to mitigate hierarchical discrepancies inherent within similarity indices encountered during dataset processing. Through the utilization of three gene expression datasets-GSE118370, GSE85841, and GSE32863sourced from the Gene Expression Omnibus (GEO), key features indicative of lung adenocarcinoma were meticulously analyzed. This methodology not only facilitates the precise categorization of data samples into lung adenocarcinoma but also enhances the reliability of the findings. The implementation of this CNN framework on the specified datasets yielded a classification accuracy of 93.32% and a precision of 94.56%, thereby surpassing the performance metrics of existing techniques. This research underscores the potential of integrating CNNs with bioinformatics for the refined classification of lung adenocarcinoma, heralding a significant step forward in the precise identification of this prevalent form of lung cancer.
International Journal of Advanced Computer Science and Applications, 2023
Cancer is the leading cause of deaths across the globe and 10 million people died of cancer and p... more Cancer is the leading cause of deaths across the globe and 10 million people died of cancer and particularly 2.21 million new cases registered besides 1.80 million deaths, according to WHO, in 2020. Malignant cancer is caused by multiplication and growth of lung cells. In this context, exploiting technological innovations for automatic detection of lung cancer early is to be given paramount importance. Towards this end significant progress has been made and deep learning model such as Convolutional Neural Network (CNN) is found superior in processing lung CT or MRI images for disease diagnosis. Lung cancer detection in the early stages of the disease helps in better treatment and cure of the disease. In this paper, we made a systematic review of deep learning methods for detection of lung cancer. It reviews peer reviewed journal papers and conferences from 2012 to 2021. Literature review throws light on synthesis of different existing methods covering machine learning (ML), deep learning and artificial intelligence (AI). It provides insights of different deep learning methods in terms of their pros and cons and arrives at possible research gaps. This paper gives knowledge to the reader on different aspects of lung cancer detection which can trigger further research possibilities to realize models that can be used in Clinical Decision Support Systems (CDSSs) required by healthcare units.
A Private Cloud Data Sharing Using Secured Group Key
International Journal of Research, 2017
The authenticated group key transfer protocol is a new protocol for creating a secure communicati... more The authenticated group key transfer protocol is a new protocol for creating a secure communication between the private cloud and the number of cloud users. The private clouds maintained by the IT organizations for their own security reasons to avoid the security attacks. The security attacks can be considered as external attacks and internal attacks. The external attacks will be a passive attacks and active attacks and we have many solutions to avoid external attacks by applying encryption algorithms to our sensitive data. The internal attacks came from the internal users in IT organizations. This paper describes the secured communication in between the private cloud and the users of the cloud to avoid internal attacks in the IT organizations.
Convolutional Neural Network based Framework for Automatic Lung Cancer Detection from Lung CT Images
2022 International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON)
international journal of engineering trends and technology, 2014
Measuring relationships between pairs of data objects in Wikipedia is challenging task in real wo... more Measuring relationships between pairs of data objects in Wikipedia is challenging task in real world data. For the Wikipedia graph, consisting of the articles together with the hyperlinks between them, the preferential attachment rule explains portion of the constitution, but instinct says that the themes of each article also performs a crucial position. This proposed system concentrate on small datasets extracted from the Wikipedia database. The matter of researching individual search space intents has attracted intensive consideration from both enterprise and academia. However, state-of-the-art intent researching techniques go through from different drawbacks when only utilizing a unmarried variety of statistics supply. For instance, query textual content has issue in distinguishing ambiguous queries; search space log is bias for a order of seek outcome and users noisy click on behaviors. In this proposed system, we'll use three kinds of similar objects, namely queries, websit...
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Papers by Mattakoyya Aharonu