Vol Machine Learning for Medical Applications: Computational Drug Discovery, Bioimaging, Smart Biomaterials

Book

Vol Machine Learning for Medical Applications

Computational Drug Discovery, Bioimaging, Smart Biomaterials

Edited by: Ranjith Rajamanickam , Amit Sharma , Dhivya Ranjith and J. Paulo Davim

Part of the multi-volume work

Machine Learning for Medical Applications Vol 1+2

Language: English

Published/Copyright: 2025

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This book is in the series

Volume 14/1 | Advanced Mechanical Engineering

About this book

Machine Learning for Medical Applications – Volume I provides an in-depth look into the frontier of artificial intelligence in healthcare, bringing together contributions from leading researchers and innovators. This volume focuses on three critical areas: computational drug discovery, advanced bioimaging techniques, and the development of smart biomaterials for medical use. Readers will discover how machine learning is revolutionizing personalized medicine, improving diagnostic accuracy, and enabling the design of AI-driven biomedical sensors and therapeutic systems. With practical insights into algorithmic modeling, drug toxicity prediction, and materials screening, this book bridges the gap between data science and clinical applications. Ideal for professionals, academics, and students in biomedical engineering, computer science, and medical informatics, this book highlights the synergistic potential of machine learning and modern medicine in shaping the future of healthcare.

Offers a thorough exploration of the intersection between machine learning and medical applications
Addresses critical healthcare challenges such as disease diagnosis, treatment optimization, patient monitoring and personalized medicine

Author / Editor information

R. Ranjith, Amit Sharma, R. Dhivya, India; J. Paulo Davim, Portugal.

Topics

Frontmatter Publicly Available Download PDF	I
Contents Publicly Available Download PDF	V
List of contributors Requires Authentication Unlicensed Licensed	VII
Blockchain technology to secure medical data sharing in machine learning applications ensure privacy and integrity M. Parthiban, P. Krishnamoorthy, D. Amaravathi, K. Suresh and S. Karthikeyan Requires Authentication Unlicensed Licensed	1
AI-powered sensors and devices for sustained health tracking P. Prasant, Kiran Siripuri, S. B. Mohan, Venkatesan Hariram and A.S. Vigneshwar Requires Authentication Unlicensed Licensed	39
Development of AI-driven biomedical sensors and devices optimization for continuous health monitoring T. Sripriya, Praveen Talari, T.M. Amirthalakahmi, B Senthilkumar and T.M. Thiyagu Requires Authentication Unlicensed Licensed	89
Design and development of AI-driven biomedical sensors and devices and their optimization for continuous health monitoring A. Aalan Babu, R. Selvakumar, D. Shobana, S. Kavitha and P.R. Therasa Requires Authentication Unlicensed Licensed	131
Machine learning-driven personalized medicine: customized drug delivery systems and patient-specific material applications B. Yamini, R. M. Dilip Charaan, G. Janani, S. Sree Dharinya and G. Parthasarathy Requires Authentication Unlicensed Licensed	193
Personalized medicine using customized drug delivery systems and patient-specific material solutions, enabled by machine learning algorithms P. Nagarajan and D. David Neels Ponkumar Requires Authentication Unlicensed Licensed	239
AI-driven drug design exploring molecular docking and lead optimization using machine learning algorithms A. Muniyappan, D.M. Kalai Selvi, S. Ramkumar, K. Suresh Kumar and Ezhil E. Nithila Requires Authentication Unlicensed Licensed	297
Machine learning models for predicting drug toxicity and side effects Amit Sharma, G. L. Karthik, Rakhi Kamra, S. Praveena and Venkatesan Hariram Requires Authentication Unlicensed Licensed	335
Machine learning innovations in biomedical materials from drug discovery to personalized medicine P. Nagarajan and D. David Neels Ponkumar Requires Authentication Unlicensed Licensed	395
High-throughput screening for novel medical materials: machine learning-enabled approaches Spoorthi P. Shetty, N. Pragadish, Ashish Verma and K.N.V. Satyanarayana Requires Authentication Unlicensed Licensed	445
Automated materials characterization using machine learning for screening biocompatible materials V. Vaishnavi, G. Meena, Santhanalakshmi, R. Anitha and K. Sivakumar Requires Authentication Unlicensed Licensed	489
Machine learning algorithms for enhanced medical image analysis and diagnostics P. Prasant, J. Dafni Rose, G. Pradeepkumar, T. Shanmugaraja and P. Janardhan Saikumar Requires Authentication Unlicensed Licensed	541
Transforming healthcare with machine learning M. Mahalakshmi, S. Sujatha, S. Banumathi, V. Purushothaman and K. Suresh Kumar Requires Authentication Unlicensed Licensed	585
Revolutionizing healthcare G. Jenifa, R. Meenal, A. Anandh, R. Jennie Bharathi and S. Sree Dharinya Requires Authentication Unlicensed Licensed	635
Index Requires Authentication Unlicensed Licensed	687
De Gruyter Series in Advanced Mechanical Engineering Requires Authentication Unlicensed Licensed

Publishing information

Pages and Images/Illustrations in book

eBook published on:

September 22, 2025

eBook ISBN:

9783111503202

Hardcover published on:

September 22, 2025

Hardcover ISBN:

9783111503189

Pages and Images/Illustrations in book

Front matter:

10

Main content:

540

Illustrations:

59

Coloured Illustrations:

162

https://doi.org/10.1515/9783111503202

eBook ISBN: 9783111503202

Hardcover ISBN: 9783111503189

Keywords for this book

Machine Learning; Medical Applications; Material Science; Healthcare Innovation

Audience(s) for this book

Academic Libraries, Researchers, Scholars, Research Students.

Safety & product resources

Manufacturer information:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com

Vol Machine Learning for Medical Applications

Overview

About this book

Author / Editor information

Topics

Table of contents

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