Data-Driven Analytics for Healthcare (Hardcover)

Meghna Sharma

ISBN 10: 1774917602 / ISBN 13: 9781774917602

Verlag: Apple Academic Press Inc., Oakville, 2025

Beschreibung

Hardcover. 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. Discusses various solutions for the diagnosis of patients with the help of automated processes using artificial intelligence techniques and technology. Highlights the possibilities of artificial intelligence, machine learning, and deep learning techniques and various tools to correctly diagnose various medical problems. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Bestandsnummer des Verkäufers 9781774917602

Bibliografische Details

• Titel: Data-Driven Analytics for Healthcare (Hardcover)
• Verlag: Apple Academic Press Inc., Oakville
• Erscheinungsjahr: 2025
• Sprache: Englisch
• ISBN-10: 1774917602
• ISBN-13: 9781774917602
• Einband: Hardcover
• Zustand: new

Über diesen Titel

Inhaltsangabe

Discusses various solutions for the diagnosis of patients with the help of automated processes using artificial intelligence techniques and technology. Highlights the possibilities of artificial intelligence, machine learning, and deep learning techniques and various tools to correctly diagnose various medical problems.

Über die Autorin bzw. den Autor

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.