Papers by Mohnish Mahamune
Asian Journal of Organic & Medicinal Chemistry, 2022
In todays modern era Data Mining is raising polularity for being used for research purpose. The h... more In todays modern era Data Mining is raising polularity for being used for research purpose. The healthcare industry is a vital element of the economy, with the aging of population and the rising cost of healthcare services. Traditionally, the goal of IT adaptation in healthcare has been cost minimisation and payment systems. This system provides positive incremental benefits to healthcare organizations by storing patient records and drug utilization information, managing insurance payments , the bulk ordering of drugs, and streaming hospital operations such as bed assignments and admit and discharge.
The usage of data mining techniques has grown in popularity as the number of medical concerns has increased. Data mining has the potential to enhance healthcare choices and patient survival times [1]. choosing the appropriate data mining technique is the main task because accuracy is the main issue. The objective is to give exposure to a variety of data mining techniques so that the researchers can have a direction to research incurable diseases which are the costilest disease so as to save money and the lives of the patient.
To exemplify the benefits of the data mining, this study examines diseases and studies the use of data mining algorithms to predict diseases. This article looks at how data mining may be used in the healthcare field. In this study, that cancer disease data is considered for the prediction of disease identification using various data mining algorithms using SPSS Modeler.
Journal of Emerging Technologies and Innovative Research, 2019
In this paper we review the current research being utilized using the data mining methods for the... more In this paper we review the current research being utilized using the data mining methods for the analysis and forecast diagnosis of numerous diseases, underlining critical concerns, and reviewing the methods in a set of cultured practices. The motto of this review is to classify and evaluate the most frequently used by algorithms of data mining on healthcare databases. The following algorithms have been known as applications of data mining in healthcare: Decision Trees (DT’s) C4.5 and C5, Support Vector Machine (SVM), artificial neural networks (ANNs) and their Multilayer Perceptron model, Naïve Bayes, Logistic Regression, Genetic Algorithms (GAs) / Evolutionary Programming (EP), Fuzzy Rules. Review present that it’s challenging to claim one algorithm of data mining as the best appropriate for the healthcare diagnosis of diseases. At present certain algorithms achieve better than others, but there are some cases when a pipeline of the facts for said algorithms claims outcomes more operational.
International Research Journal of Engineering and Technology, 2015
Software testing is important activity in software Engineering concerned to Software Development ... more Software testing is important activity in software Engineering concerned to Software Development Life Cycle (SDLC). To reduce cost of physical testing as well as to growth consistency of it, scholars and experts have hands on to automate it. One of the essential activities in testing background is to generate test case automatically. This Literature based paper focuses on a survey of UML based automatic test case generation methods that are originate in the recent networks.
Mathematical Sciences International Research Journal, 2016
Routing metric always plays a key issue in performance of wireless mesh network. Utilizing the ro... more Routing metric always plays a key issue in performance of wireless mesh network. Utilizing the routing metric for efficient communication is always a skilled work to be done. Wireless mesh network always have its advantages to be used for forwarding the network traffic. We have examined some of the routing metrics and compared the performances under varying conditions for finding out the comparative analysis of routing protocols.
International Journal on Recent and Innovation Trends in Computing and Communication, 2014
Nowadays personal identification or verification has become one of the most prominent issues in s... more Nowadays personal identification or verification has become one of the most prominent issues in security management. In order to restrict access to secure systems multibiometric refers to authentication techniques that rely on measurable physiological and individual traits that can be automatically verified. In other words, all individuals ones have personal traits that can be used for distinctive identification purposes, including a face, fingerprint, Iris, palm print, retina and voice etc. Multibiometric systems, are projected to be more reliable due to the presence of multiple, legitimate bits of evidence. In this paper, we describe fusion techniques and performance of a multibiometric in pattern recognition and security systems. Some of the experimental results are performed on fusing on fingerprint and Iris.
CURRENT GLOBAL REVIEWER, 2018
Wireless mesh networks (WMNs) is the key technology for next-generation wireless networking. WMNs... more Wireless mesh networks (WMNs) is the key technology for next-generation wireless networking. WMNs consist of mesh routers and mesh clients, where mesh routers have minimal mobility. Due to its advantages over other wireless networks, WMNs are ongoing with rapid progress and it is inspiring a number of applications. However, many more technical issues still exist that is to be resolved for better performance. In order to provide a better understanding of challenges in WMNs, here we have provided details of WMNs. Open research issues in all protocol layers are also discussed, with an objective to spark new research interests in this field.
Advances in Computational Research, 2015
Knowledge Management (KM) in any organization in integration with information technology supports... more Knowledge Management (KM) in any organization in integration with information technology supports system strategies with busi-ness strategies to attain the vision and mission very precisely. In today’s era knowledge management is crucial in all aspects of organization; Hence knowledge discovery from massive database is today’s need. Knowledge Discovery in Databases (KDD) helps organizations turn their data collection into valuable information. Organizations that take advantage of KDD will find that they can lower the healthcare costs while improving healthcare quality by using fast and better clinical decision making. The data collected by healthcare organization might be struc-tured or unstructured. Hence it is essential to use some technology to gain knowledge from massive databases which will increase the access to knowledge for the people working in organization as well as competitiveness among organizations. Though the healthcare sector relies heavily on knowledge and evidence based medicine is expected to be implemented in daily healthcare activities; the quality of care relies on the exchanging the knowledge between the organization. The Data Mining comes up against major scientific and technological type of tool for knowledge discovery and is also considered as significant field in Knowledge Management. This paper explores the Data Mining techniques which found suitable for discovering the hidden knowledge from the healthcare massive database and their applications which supports the KM process in healthcare sector, its advantages, disadvantages and challenges.
Asian Jouranl of Organic & Medicinal Chemistry, 2022
In todays modern era Data Mining is rising popularity for being used for research purpose. The he... more In todays modern era Data Mining is rising popularity for being used for research purpose. The healthcare industry is a vital element of economy, with aging of the population and the rising cost of healthcare services. Traditionally, the goal of IT adoption in healthcare has been cost minimization and payment systems. This system provides positive incremental benefits to healthcare organizations by storing patient records and drug utilization information, managing insurance payments, the bulk ordering of drugs and streamlining hospital operations such as bed assignments and admit and discharges.
The usage of data mining techniques has grown in popularity as the number of medical concerns has increased. Data Mining has the potential to enhance healthcare choices and patient survival times. Choosing the appropriate data mining techniques is the main tasks because the accuracy is the main issue. Earlier diagnosis done was based on the doctors experience or expertise but still, wrong cases were reported. The objective is to give exposure to variety of data mining techniques so that the researchers can have a direction to research incurable diseases which are the costliest diseases so as to save money and lives of the patient.
To exemplify the benefits of data mining, this study examines disease data and studies the use of data mining algorithms to predict diseases. This artical looks at how data mining may be used in the healthcare field. In this study, the cancer disease data is considered for the prediction of diseases identification using various data mining algorithms using the SPSS Modeler.
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Papers by Mohnish Mahamune
The usage of data mining techniques has grown in popularity as the number of medical concerns has increased. Data mining has the potential to enhance healthcare choices and patient survival times [1]. choosing the appropriate data mining technique is the main task because accuracy is the main issue. The objective is to give exposure to a variety of data mining techniques so that the researchers can have a direction to research incurable diseases which are the costilest disease so as to save money and the lives of the patient.
To exemplify the benefits of the data mining, this study examines diseases and studies the use of data mining algorithms to predict diseases. This article looks at how data mining may be used in the healthcare field. In this study, that cancer disease data is considered for the prediction of disease identification using various data mining algorithms using SPSS Modeler.
The usage of data mining techniques has grown in popularity as the number of medical concerns has increased. Data Mining has the potential to enhance healthcare choices and patient survival times. Choosing the appropriate data mining techniques is the main tasks because the accuracy is the main issue. Earlier diagnosis done was based on the doctors experience or expertise but still, wrong cases were reported. The objective is to give exposure to variety of data mining techniques so that the researchers can have a direction to research incurable diseases which are the costliest diseases so as to save money and lives of the patient.
To exemplify the benefits of data mining, this study examines disease data and studies the use of data mining algorithms to predict diseases. This artical looks at how data mining may be used in the healthcare field. In this study, the cancer disease data is considered for the prediction of diseases identification using various data mining algorithms using the SPSS Modeler.