Healthcare Solutions Using Machine Learning and Informatics covers novel and innovative solutions for healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, and intelligent IoT-based solutions for medical image analysis, medical big-data processing, and disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence.
The wide variety of topics covered include:
Artificial Intelligence in healthcare
Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19
Big data analytics solutions for healthcare data processing
Reliable biomedical applications using AI models
Intelligent IoT in healthcare
The book explains fundamental concepts as well as the advanced use cases, illustrating how to apply emerging technologies such as machine learning, AI models, and data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. Chapters contributed by noted academicians and professionals examine various solutions, frameworks, applications, case studies, and best practices in the healthcare domain.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für Beruf und Forschung
Academic
Illustrationen
8 s/w Photographien bzw. Rasterbilder, 14 Farbfotos bzw. farbige Rasterbilder, 12 s/w Zeichnungen, 70 farbige Zeichnungen, 20 s/w Abbildungen, 84 farbige Abbildungen
70 Line drawings, color; 12 Line drawings, black and white; 14 Halftones, color; 8 Halftones, black and white; 84 Illustrations, color; 20 Illustrations, black and white
Maße
Höhe: 234 mm
Breite: 156 mm
Dicke: 15 mm
Gewicht
ISBN-13
978-1-032-34522-2 (9781032345222)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Dr. Punit Gupta is an Associate Professor in the Department of Computer and Communication Engineering at Manipal University, Jaipur, India.
Dr. Dinesh Kumar Saini is a Professor in the Department of Computer and Communication Engineering at Manipal University, Jaipur, India.
Dr. Rohit Verma is affiliated with the INSIGHT Research Lab SFI, Dublin City University, Dublin, Ireland.
Herausgeber*in
Pandit DeenDayal Energy University, India
1. Introduction to Artificial Intelligence in Healthcare 2. Machine Learning in Radio Imagining 3. Solutions Using Machine Learning for Diabetes 4. A Highly Reliable Machine Learning Algorithm for Cardiovascular Disease Prediction 5. Machine Learning Algorithm for Industry Using Image Sensing 6. Solutions Using Machine Learning For COVID-19 7. Big Data Analytics in Healthcare Data Processing 8. Reliable Biomedical Applications Using AI Models 9. Disease Detection Using Imaging Sensors, Deep Learning and Machine Learning for Smart Farming 10. IoT Application for Healthcare 11. Machine Learning Algorithm for Diabetes Disease Prediction 12. Use of Machine Learning in Healthcare
