<?xml version="1.0" encoding="UTF-8"?>
<feed xmlns="http://www.w3.org/2005/Atom" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <title>DSpace Collection:</title>
  <link rel="alternate" href="http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/15" />
  <subtitle />
  <id>http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/15</id>
  <updated>2026-04-24T20:54:51Z</updated>
  <dc:date>2026-04-24T20:54:51Z</dc:date>
  <entry>
    <title>Machine learning in expert systems for disease diagnostics in human healthcare</title>
    <link rel="alternate" href="http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8319" />
    <author>
      <name>Yadava, Arvind Kumar</name>
    </author>
    <author>
      <name>Shuklaa, Rohit</name>
    </author>
    <author>
      <name>Singh, Tiratha Raj</name>
    </author>
    <id>http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8319</id>
    <updated>2022-11-16T07:02:51Z</updated>
    <published>2021-01-01T00:00:00Z</published>
    <summary type="text">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&#xD;
are continually leading to tremendous advances in healthcare. The definition of healthcare is the improvement&#xD;
of health through prevention, treatment, and inspection of diseases (Toli and Murtagh,&#xD;
2020). Accurate diagnosis is essential for medical treatment and decision-making, but it can be difficult&#xD;
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.&#xD;
Physician control is an effective solution for diagnosis and treatment, but it is costly. Artificial intelligence&#xD;
(AI) seems particularly well suited for this application (Davenport and Kalakota, 2019).</summary>
    <dc:date>2021-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Advances in Patch Antenna Design Using EBG Structures</title>
    <link rel="alternate" href="http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8318" />
    <author>
      <name>Thakur, Ekta</name>
    </author>
    <author>
      <name>Jaglan, Naveen</name>
    </author>
    <author>
      <name>Gupta, Samir Dev</name>
    </author>
    <id>http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8318</id>
    <updated>2022-11-16T06:58:48Z</updated>
    <published>2020-01-01T00:00:00Z</published>
    <summary type="text">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&#xD;
advanced form of electromagnetic materials. The development of “metamaterials”&#xD;
with unique features has recently gained great attention from the researchers [1].&#xD;
Metamaterials are used in many fields such as optics, nanoscience, material science.</summary>
    <dc:date>2020-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Taxonomy on Machine Learning Based Techniques to Identify the Heart Disease</title>
    <link rel="alternate" href="http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8317" />
    <author>
      <name>Srivastava, Anand Kumar</name>
    </author>
    <author>
      <name>Singh, Pradeep Kumar</name>
    </author>
    <author>
      <name>Kumar, Yugal</name>
    </author>
    <id>http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8317</id>
    <updated>2022-11-16T06:52:11Z</updated>
    <published>2019-01-01T00:00:00Z</published>
    <summary type="text">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&#xD;
Heart Disease or Cardiovascular diseases (CVDs), which is 31% of all global&#xD;
deaths reflected in Survey of World Heart Day 2017 [33]. In September 2016,&#xD;
many countries have taken the various Global Hearts Initiative in prediction and&#xD;
diagnosis of heart Diseases at earlier stages so that it can be cure perfectly [5].&#xD;
Many authors have studied in this filed to optimize the performance of various&#xD;
ML techniques using various approaches. In latest studies, many groups have&#xD;
uncovered that many optimization algorithm like Differential Evolution, Genetic&#xD;
Variants, and Particle Swarm optimization are associated with prediction algorithm&#xD;
like K-Nearest neighbor, Decision Tree, Neural Network, Support Vector&#xD;
machine, Logistic Regression etc. to make efficient medical system for CVDs.&#xD;
The Objective of our current study is to analyze the comparatively study of the&#xD;
ML techniques in terms of performance measure of different ML techniques that&#xD;
have been used by various authors in their research work in earlier studies of&#xD;
heart disease prediction and diagnosis process.</summary>
    <dc:date>2019-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>A novel approach for securing e-health application in a cloud environment</title>
    <link rel="alternate" href="http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8316" />
    <author>
      <name>Kumar, Dipesh</name>
    </author>
    <author>
      <name>Mandala, Nirupama</name>
    </author>
    <author>
      <name>Kumar, Kumar</name>
    </author>
    <id>http://www.ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8316</id>
    <updated>2022-11-16T06:48:01Z</updated>
    <published>2021-01-01T00:00:00Z</published>
    <summary type="text">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&#xD;
the portable mobile devices (Mumrez et al., 2019). Due to development of internet and its users across&#xD;
the world, there is a demand of centralized healthcare information system. Rapid increase in chronic&#xD;
diseases and various disease aspects, disease prevention, and various government policies of providing&#xD;
a better healthcare facility to its citizens steadily increased the demand for intelligent and portable&#xD;
mobile-based services (Sravani et al., 2017). In the past one decade, the use of smart phones has increased&#xD;
and the same can be utilized for e-Health services and can be used for providing personal health&#xD;
record (PHR), disease-related information and other self-heathcare facilities ( Jung and Chung, 2016).</summary>
    <dc:date>2021-01-01T00:00:00Z</dc:date>
  </entry>
</feed>

