Data-Driven Analytics for Healthcare
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Data-Driven Analytics for Healthcare: Artificial Intelligence and Machine Learning for Medical Diagnostics

Data-Driven Analytics for Healthcare: Artificial Intelligence and Machine Learning for Medical Diagnostics


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About the Book

The new book highlights the application of artificial intelligence, machine learning, and deep learning techniques to diagnose medical problems. General predictive analysis methods are explained in disease detection applications along with machine learning techniques for the implementation of predictive analysis methods. The book covers object detection approaches for diseases such as pneumonia, application of monitoring and tracking the coronavirus disease, various endodontic applications for handling diagnostic abnormalities using deep learning methods, applications of healthcare for human activity recognition, and more.

Table of Contents:
Introduction 1. Predictive and Descriptive Analytics in Healthcare 2. Biomimetics and Mind-Machine Interface: The Human Brain as a Quantum Computer 3. The Inevitable Artificial Intelligence Revolution in Healthcare 4. Object Detection Approach for Pneumonia Detection Using X-Ray Images 5. Corona Tracker: An Application for Monitoring and Tracking Corona Disease 6. Investigation on Diagnosing Irregularities in Endodontic Applications Using Deep Learning Methods 7. Teknomo–Fernandez Kernelized Discriminant Analysis-Based Connectionist Deep Multilayer Perceptive Neural Learning for Human Activity Recognition 8. Transforming Healthcare with AI: An Adequate Method for Diabetes Prediction Using Machine Learning Techniques 9. A Survey on Artificial Intelligence and Machine Learning Approaches for Medical Data Authentication 10. Data-Driven Analytics for Healthcare: Artificial Intelligence and Machine Learning for Medical Diagnostics 11. M-Blockchain: A Futuristic Approach for Healthcare 12. Blockchain in Healthcare: Evolution, Applications, and Challenges

About the Author :
Meghna Sharma, PhD, is an Associate Professor and Data Science Specialisation Lead in the Department of Computer Science and Engineering at The NorthCap University, Gurugram, India. She has more than 20 years of teaching, research, and administration experience. She earlier worked as a scientist in the Control Systems Group, ISRO Satellite Center, Bangalore. She is a recipient of “Award for Science” conferred by Govt. of Haryana. She has published 35 research papers and three international patents and two national patents in the AI domain. Priyanka Vashisht, PhD, is an Associate Professor of Computer Science and Engineering at Amity University Haryana, Gurugram, India. She has more than 19 years of teaching, research, and administration experience. She is a faculty sponsor for the ACM Students Chapter. She has published many research papers in journals and conferences as well as book chapters. She has two Indian and two international patents in her name. She has chaired international conferences and is a reviewer for many national and international conferences and journals. A. V. Senthil Kumar, PhD, has five years of industrial experience and 27 years of teaching experience. He has published book chapters, papers in international and national journals and conferences, and several edited books. He is an Associate Editor of IEEE Access and a key member for the Machine Intelligence Research Lab, India. Professor Kumar is an editorial board member and reviewer for various international journals. He is also a committee member for various international conferences. Chitra Singh, PhD, is a Professor of Chemistry Education and Environmental Education, National Council of Educational Research and Training, Bhopal, Madhya Pradesh, India, for more than 22 years. Dr. Singh has published more than 40 papers in various journals, completed eight research projects, conducted 25 training programs, and developed 20 curriculum materials. Abdelmalek Amine, PhD, is a Professor of Computer Science at the University of Saida Dr. Moulay Tahar, Algeria, where he is also Director of the Knowledge Management and Complex Data Laboratory and Vice Rector of External Relations and Cooperation. His research interests include big data, IoT, data mining, text mining, ontology, classification, clustering, neural networks, and biomimetic optimization methods. He has several publications in the field of AI and is on the editorial boards of eminent international journals.


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Product Details
  • ISBN-13: 9781040229484
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Apple Academic Press Inc.
  • Language: English
  • ISBN-10: 1040229484
  • Publisher Date: 10 Feb 2025
  • Binding: Digital (delivered electronically)
  • Sub Title: Artificial Intelligence and Machine Learning for Medical Diagnostics


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