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Artificial Intelligence and Machine Learning in Healthcare

  • Book
  • © 2021

Overview

Editors:
  1. Ankur Saxena

    1. Amity University, Noida, India

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  2. Shivani Chandra

    1. Amity University, Noida, India

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    You can also search for this editor in PubMed   Google Scholar

  • Analyzes the applications of artificial intelligence and machine learning in healthcare

  • Discusses the role of artificial intelligence in disease prognosis and management

  • Explores the role of AI in personalized and precision medicine

  • Introduce the concept of BIAS in Big Data and machine learning

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xv
    Download chapter PDF

  2. Practical Applications of Artificial Intelligence for Disease Prognosis and Management

    • Ankur Chaurasia, Sakshi Vats, Abhishek Sengupta, Abhay Bansal, Priyanka Narad
    Pages 1-36

  3. Automated Diagnosis of Diabetes Mellitus Based on Machine Learning

    • Manish Edida, N. Jaya Lakshmi, Neetu Jabalia
    Pages 37-56

  4. Artificial Intelligence in Personalized Medicine

    • Khammampalli Srija, P. P. R. Prithvi, Ankur Saxena, Alka Grover, Shivani Chandra, Shalini Jauhari Jain
    Pages 57-69

  5. Artificial Intelligence in Precision Medicine: A Perspective in Biomarker and Drug Discovery

    • Seneha Santoshi, Dipankar Sengupta
    Pages 71-88

  6. Transfer Learning in Biological and Health Care

    • Robin Sinha, Ankur Saxena, Smitha Mony Sreedharan
    Pages 89-98

  7. Visualization and Prediction of COVID-19 Using AI and ML

    • Dilip Kumar J. Saini, Dhirendra Siddharth, Ajay Kumar
    Pages 99-112

  8. Machine Learning Approaches in Detection and Diagnosis of COVID-19

    • S. Suba, Nita Parekh
    Pages 113-145

  9. Applications of Machine Learning Algorithms in Cancer Diagnosis

    • Amita Sharma, Shalini Jain, Sreemoyee Chatterjee
    Pages 147-181

  10. Use of Artificial Intelligence in Research and Clinical Decision Making for Combating Mycobacterial Diseases

    • Mukul Sharma, Pushpendra Singh
    Pages 183-215

  11. Bias in Medical Big Data and Machine Learning Algorithms

    • Ankur Saxena, Mohit Saxena, Alejandra Rodriguez Ilerena
    Pages 217-228

  12. Correction to: Artificial Intelligence and Machine Learning in Healthcare

    • Ankur Saxena, Shivani Chandra
    Pages C1-C1
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Keywords

About this book

This book reviews the application of artificial intelligence and machine learning in healthcare.  It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19.  The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence.  The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples.  Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.

Editors and Affiliations

  • Amity University, Noida, India

    Ankur Saxena, Shivani Chandra

About the editors

Dr. Ankur Saxena is currently working as an Assistant Professor at Amity University, Noida, Uttar Pradesh. He has been teaching graduate and post-graduate students for more than 15 years and 3 years of industrial experience in software development. He has published 5 books and more than 40 research articles in reputed journals and is an editorial board member and reviewer for several journals. His research interests include cloud computing, big data, machine learning, evolutionary algorithms, software frameworks, design & analysis of algorithms, and biometric identification.


Dr. Shivani Chandra is an Assistant Professor at Amity Institute of Biotechnology, Amity University, Uttar Pradesh, Noida. She has more than 20 years of experience in biotechnology and molecular biology. Her research interests includes genomics analysis, computational biology, and bioinformatics data analysis. She has submitted more than 4000 clones to the NCBI GenBank and was one of the key players in the Rice Genome Sequencing Project. She has published several research articles in genome sequencing, comparative genomics, and genome analysis in reputed journals. She has more than 15 years of teaching experience in computational biology, molecular biology, genetics, recombinant DNA Technology, and bioinformatics.


Bibliographic Information

  • Book Title: Artificial Intelligence and Machine Learning in Healthcare

  • Editors: Ankur Saxena, Shivani Chandra

  • DOI: https://doi.org/10.1007/978-981-16-0811-7

  • Publisher: Springer Singapore

  • eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

  • Hardcover ISBN: 978-981-16-0810-0Published: 07 May 2021

  • Softcover ISBN: 978-981-16-0813-1Published: 08 May 2022

  • eBook ISBN: 978-981-16-0811-7Published: 06 May 2021

  • Edition Number: 1

  • Number of Pages: XV, 228

  • Number of Illustrations: 31 b/w illustrations, 88 illustrations in colour

  • Topics: Bioinformatics, Health Care Management, Medicine/Public Health, general, Artificial Intelligence

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