1st Edition

Artificial Intelligence in Medicine

Edited By Thompson Stephan Copyright 2025
264 Pages 152 B/W Illustrations
by CRC Press

264 Pages 152 B/W Illustrations
by CRC Press

264 Pages 152 B/W Illustrations
by CRC Press

In the ever-evolving realm of healthcare, Artificial Intelligence in Medicine emerges as a trailblazing guide, offering an extensive exploration of the transformative power of Artificial Intelligence (AI). Crafted by leading experts in the field, this book sets out to bridge the gap between theoretical understanding and practical application, presenting a comprehensive journey through the... Read more

List of Contributors
PART 1. Foundations of AI in healthcare
1. Exploring deep learning approaches for cardiac arrhythmia diagnosis
M S SUPRIYA, L YASHASWINI, AND K S ARVIND

2. Neural networks and LDA-based machine learning framework for the early detection of breast cancer
SAANJHI SARAOGI, SAKSHI SARAOGI, ASNATH VICTY PHAMILA Y, AND KALAIVANI KATHIRVELU

3. Advanced deep learning algorithms for early ocular disease detection using fundus images
SHUBHASHREE A, DIVYA B S, AND THOMPSON STEPHAN

PART 2. Disease detection and diagnosis

4. A vision transformer-based approach for brain tumor detection
PIYUSH KUMAR, RADHIKA GOYAL, SHUBHAM GARG, SHUCHI MALA, RONIT BALI, AND ANUKANSHA SHARMA

5. Early detection of skin cancer through human-computer collaboration
PIYUSH KUMAR, RISHI CHAUHAN, ACHYUT SHANKAR, AND THOMPSON STEPHAN

6. Improved mass detection in mammogram images with Dual Tree Complex Wavelet Transform and Fourier Descriptors
M KANCHANA, R NARESH, C N S VINOTH KUMAR, AND P PANDIARAJA

7. A deep learning-based model for early detection of COVID-19 using chest X-ray images
S PUNITHA, VAISHALI R KULKARNI, AND THOMPSON STEPHAN

8. Detection of seizure activity in fMRI images using deep learning techniques
ABHISHEK SAIGIRIDHARI, ABHISHEK MISHRA, ADITI MAHADWARE, AARYA TUPE, AND DHANALEKSHMI YEDURKAR

PART 3. Disease prediction and public health

9. Improving prediction accuracy for neo-adjuvant chemotherapy response in breast cancer through 3D image segmentation and deep learning techniques
K V RANJITHA AND T P PUSHPHAVATHI

10. A machine learning predictive framework for diabetes management using blood parameters
A POONGUZHALI, P RAMKUMAR, REJI THOMAS, S TAMIL SELVAN, AND ANGEL LATHA MARY

11. A combined neuro-fuzzy and Naive Bayes approach for swine flu disease prediction
P SANTHI, M SATHYA SUNDARAM, AND P PANDIARAJA

12. Enhancing decision-making in maternal public healthcare using a knowledge discovery-based predictive analytics framework
SHELLY GUPTA, JYOTI AGARWAL, AND DISHA MOHINI PATHAK

PART 4. Patient care and enhancements

13. Enhancing patient care and treatment through explainable AI: A gap analysis
SHYNI CARMEL MARY S, DHYANA SHARON ROSS, ANBUMANI BALA, AND JOE ARUN

14. Improved medical image captioning for chest X-rays using a hybrid VGG-ELECTRA model
J LIMSA JOSHI, J CHRISTINA, L REMEGIUS PRAVEEN SAHAYARAJ, V J SHARMILA, AND ASHWIN BALASUBRAMANIAN

15. Diagnosing Parkinson’s disease using a deep learning model based on electromyography sensors
P PADMA PRIYA DHARISHINI, B R KARTHIKEYAN, SURYA TEJAS V, JASH SINGH, SUMUKHA BHAT, AND G KARTHIK

16. Enhancing heart disease prediction with Hybridized KNN-MOPSO algorithm
R MANORANJITHAM, S PUNITHA, AND THOMPSON STEPHAN

Index

Biography

Thompson Stephan earned his Ph.D. in Computer Science and Engineering from Pondicherry University, India, in 2018. Currently serving as an Associate Professor in the Department of Computer Science & Engineering at Graphic Era Deemed to be University, Dehradun, Uttarakhand, India, he achieved recognition among the world's top 2% most influential scientists for 2023, a distinction jointly conferred by Elsevier and Stanford University, USA. Acknowledged for academic excellence during his master's degree, he secured a university rank. Additionally, he was honored with the Best Researcher Award-2020 and the Protsahan Research Award in 2023 by the IEEE Bangalore Section, India. His research interests primarily focus on implementing and applying artificial intelligence techniques in practical settings. He has authored numerous technical research papers published in renowned journals and conferences by IEEE, Elsevier, Springer, and others. Actively serving as a reviewer for esteemed international journals and working as a book editor, Thompson Stephan is dedicated to advancing the field.