http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/15 2026-04-24T20:54:51Z http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8319 Title: Machine learning in expert systems for disease diagnostics in human healthcare Authors: Yadava, Arvind Kumar; Shuklaa, Rohit; Singh, Tiratha Raj Abstract: Good health is an important aspect of quality of life, as nothing is more valuable, and new technologies are continually leading to tremendous advances in healthcare. The definition of healthcare is the improvement of health through prevention, treatment, and inspection of diseases (Toli and Murtagh, 2020). Accurate diagnosis is essential for medical treatment and decision-making, but it can be difficult to identify a specific disease from the stated symptoms of a patient, due to the inexact informationprovided. Thus the main job in medical diagnosis is to use expert logical reasoning to make decisions. Physician control is an effective solution for diagnosis and treatment, but it is costly. Artificial intelligence (AI) seems particularly well suited for this application (Davenport and Kalakota, 2019). 2021-01-01T00:00:00Z http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8318 Title: Advances in Patch Antenna Design Using EBG Structures Authors: Thakur, Ekta; Jaglan, Naveen; Gupta, Samir Dev Abstract: High-performance applications in wireless communication systems require an advanced form of electromagnetic materials. The development of “metamaterials” with unique features has recently gained great attention from the researchers [1]. Metamaterials are used in many fields such as optics, nanoscience, material science. 2020-01-01T00:00:00Z http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8317 Title: Taxonomy on Machine Learning Based Techniques to Identify the Heart Disease Authors: Srivastava, Anand Kumar; Singh, Pradeep Kumar; Kumar, Yugal Abstract: Every year average death of human being is 17.7 million caused by Heart Disease or Cardiovascular diseases (CVDs), which is 31% of all global deaths reflected in Survey of World Heart Day 2017 [33]. In September 2016, many countries have taken the various Global Hearts Initiative in prediction and diagnosis of heart Diseases at earlier stages so that it can be cure perfectly [5]. Many authors have studied in this filed to optimize the performance of various ML techniques using various approaches. In latest studies, many groups have uncovered that many optimization algorithm like Differential Evolution, Genetic Variants, and Particle Swarm optimization are associated with prediction algorithm like K-Nearest neighbor, Decision Tree, Neural Network, Support Vector machine, Logistic Regression etc. to make efficient medical system for CVDs. The Objective of our current study is to analyze the comparatively study of the ML techniques in terms of performance measure of different ML techniques that have been used by various authors in their research work in earlier studies of heart disease prediction and diagnosis process. 2019-01-01T00:00:00Z http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8316 Title: A novel approach for securing e-health application in a cloud environment Authors: Kumar, Dipesh; Mandala, Nirupama; Kumar, Kumar Abstract: With the rapid increase in convergence technologies, the world is able to get lot of information through the portable mobile devices (Mumrez et al., 2019). Due to development of internet and its users across the world, there is a demand of centralized healthcare information system. Rapid increase in chronic diseases and various disease aspects, disease prevention, and various government policies of providing a better healthcare facility to its citizens steadily increased the demand for intelligent and portable mobile-based services (Sravani et al., 2017). In the past one decade, the use of smart phones has increased and the same can be utilized for e-Health services and can be used for providing personal health record (PHR), disease-related information and other self-heathcare facilities ( Jung and Chung, 2016). 2021-01-01T00:00:00Z