AI and Data Science in Medical Research
Published on 8. May 2026
Book
Paperback/Softback
284 pages
978-0-443-27638-5 (ISBN)
Description
AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies.
The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.
The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.
More details
Series
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
College/higher education
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 235 mm
Width: 191 mm
Weight
450 gr
ISBN-13
978-0-443-27638-5 (9780443276385)
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 Classification
Other editions
Additional editions
Olfa Boubaker
AI and Data Science in Medical Research
E-Book
04/2026
Elsevier
€166.99
Available for download
Person
Olfa Boubaker is a Full Professor at the National Institute of Applied Sciences and Technology (INSAT) at the University of Carthage, Tunisia. Her research spans control theory, nonlinear systems, and robotics, with a focus on healthcare applications and human-centered technologies. She received her PhD in Electrical Engineering from the National Engineering School of Tunis (ENIT) and Habilitation Universitaire degree in Control Engineering from the National Engineering School of Sfax (ENIS), in Tunisia. Professor Boubaker leads interdisciplinary research projects at the interface of medicine and technology and serves as Series Editor of Medical Robots and Devices: New Developments and Advances. She has authored over 150 peer-reviewed papers and several books, and is an Associate Editor for Robotica and the International Journal of Advanced Robotic Systems. She also contributes to various scientific journals and mentors numerous engineering graduates.
Content
AI and Data Science in Medical Research: An Overview
Part I: Foundations and Core Technologies
1. Medical Data Foundations: Key Concepts and Definitions for Clinicians and Researchers
2. Artificial Intelligence in Medical Research: Fundamental Methods, Techniques, and Clinical Applications
Part II: AI-Driven Diagnosis and Patient Monitoring
3. Artificial Intelligence in Neuroimaging: from data acquisition to data analysis
4. Synthetic Data for Melanoma Detection: Generative Adversarial Networks and Diffusion Models in Practice
5. Voice-Based Deep Learning for Parkinson's Disease Diagnosis
6. Modeling Mpox Transmission Dynamics: Deterministic Approaches Linking Environment and Host Interactions
Part III: Therapeutics, Genomics, and Ethical Perspectives
7. AI for Drug Discovery and Development
8. Revolutionizing Genomic Medicine with AI and Data Analytics
9. AI-Powered Pipelines for Therapeutic Innovation
10. Conclusions and Future Directions: Challenges, Opportunities, and Ethical Considerations in AI-Driven Medical Research
Part I: Foundations and Core Technologies
1. Medical Data Foundations: Key Concepts and Definitions for Clinicians and Researchers
2. Artificial Intelligence in Medical Research: Fundamental Methods, Techniques, and Clinical Applications
Part II: AI-Driven Diagnosis and Patient Monitoring
3. Artificial Intelligence in Neuroimaging: from data acquisition to data analysis
4. Synthetic Data for Melanoma Detection: Generative Adversarial Networks and Diffusion Models in Practice
5. Voice-Based Deep Learning for Parkinson's Disease Diagnosis
6. Modeling Mpox Transmission Dynamics: Deterministic Approaches Linking Environment and Host Interactions
Part III: Therapeutics, Genomics, and Ethical Perspectives
7. AI for Drug Discovery and Development
8. Revolutionizing Genomic Medicine with AI and Data Analytics
9. AI-Powered Pipelines for Therapeutic Innovation
10. Conclusions and Future Directions: Challenges, Opportunities, and Ethical Considerations in AI-Driven Medical Research