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.

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Publicly Available

Frontmatter
I

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Contents
V

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List of contributors
VII

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Blockchain technology to secure medical data sharing in machine learning applications ensure privacy and integrity
1
M. Parthiban, P. Krishnamoorthy, D. Amaravathi, K. Suresh and S. Karthikeyan

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AI-powered sensors and devices for sustained health tracking
39
P. Prasant, Kiran Siripuri, S. B. Mohan, Venkatesan Hariram and A.S. Vigneshwar

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Development of AI-driven biomedical sensors and devices optimization for continuous health monitoring
89
T. Sripriya, Praveen Talari, T.M. Amirthalakahmi, B Senthilkumar and T.M. Thiyagu

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Design and development of AI-driven biomedical sensors and devices and their optimization for continuous health monitoring
131
A. Aalan Babu, R. Selvakumar, D. Shobana, S. Kavitha and P.R. Therasa

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Machine learning-driven personalized medicine: customized drug delivery systems and patient-specific material applications
193
B. Yamini, R. M. Dilip Charaan, G. Janani, S. Sree Dharinya and G. Parthasarathy

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Personalized medicine using customized drug delivery systems and patient-specific material solutions, enabled by machine learning algorithms
239
P. Nagarajan and D. David Neels Ponkumar

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AI-driven drug design exploring molecular docking and lead optimization using machine learning algorithms
297
A. Muniyappan, D.M. Kalai Selvi, S. Ramkumar, K. Suresh Kumar and Ezhil E. Nithila

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Machine learning models for predicting drug toxicity and side effects
335
Amit Sharma, G. L. Karthik, Rakhi Kamra, S. Praveena and Venkatesan Hariram

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Machine learning innovations in biomedical materials from drug discovery to personalized medicine
395
P. Nagarajan and D. David Neels Ponkumar

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High-throughput screening for novel medical materials: machine learning-enabled approaches
445
Spoorthi P. Shetty, N. Pragadish, Ashish Verma and K.N.V. Satyanarayana

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Automated materials characterization using machine learning for screening biocompatible materials
489
V. Vaishnavi, G. Meena, Santhanalakshmi, R. Anitha and K. Sivakumar

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Machine learning algorithms for enhanced medical image analysis and diagnostics
541
P. Prasant, J. Dafni Rose, G. Pradeepkumar, T. Shanmugaraja and P. Janardhan Saikumar

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Transforming healthcare with machine learning
585
M. Mahalakshmi, S. Sujatha, S. Banumathi, V. Purushothaman and K. Suresh Kumar

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Revolutionizing healthcare
635
G. Jenifa, R. Meenal, A. Anandh, R. Jennie Bharathi and S. Sree Dharinya

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Index
687

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De Gruyter Series in Advanced Mechanical Engineering

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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

Frontmatter

Contents

List of contributors

Blockchain technology to secure medical data sharing in machine learning applications ensure privacy and integrity

AI-powered sensors and devices for sustained health tracking

Development of AI-driven biomedical sensors and devices optimization for continuous health monitoring

Design and development of AI-driven biomedical sensors and devices and their optimization for continuous health monitoring

Machine learning-driven personalized medicine: customized drug delivery systems and patient-specific material applications

Personalized medicine using customized drug delivery systems and patient-specific material solutions, enabled by machine learning algorithms

AI-driven drug design exploring molecular docking and lead optimization using machine learning algorithms

Machine learning models for predicting drug toxicity and side effects

Machine learning innovations in biomedical materials from drug discovery to personalized medicine

High-throughput screening for novel medical materials: machine learning-enabled approaches

Automated materials characterization using machine learning for screening biocompatible materials

Machine learning algorithms for enhanced medical image analysis and diagnostics

Transforming healthcare with machine learning

Revolutionizing healthcare

Index

De Gruyter Series in Advanced Mechanical Engineering

Bibliographic data