Overview

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.

Full Product Details

Author:   Olfa Boubaker, PhD (Full Professor, National Institute of Applied Sciences and Technology (INSAT), University of Carthage, Tunisia)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Weight:   0.450kg
ISBN:  

9780443276385

ISBN 10:   0443276382
Pages:   450
Publication Date:   01 May 2026
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available  
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Table of Contents

Introduction to AI and Data Science in Medical Research Part 1. Drug Discovery and Development 1. Drug Discovery and Development: Leveraging AI and data science to accelerate the discovery of novel therapeutic compounds and optimize drug development pipelines 2. Artificial Intelligence and Data Science in Drug Discovery and Development 3. Leveraging AI and Data Science to accelerate the discovery of novel therapeutic compounds and optimize drug development pipelines Part 2. Medical Imaging and Diagnostics 4. Advancements in Medical Imaging: Harnessing AI for Early Disease Detection and Diagnosis 5. Artificial Intelligence in Neuroimaging: from data acquisition to data analysis Part 3. Genomic Medicine 6. Comprehensive Review of Distributed Deep Learning Approaches for Genomics Analysis 7. Revolutionizing Genomic Medicine with AI and Data Analytics Part 4. Public Health Surveillance 8. Dataset on the COVID-19 Pandemic Situation in Tunisia with application to SIR Model 9. Harnessing AI for Enhanced Public Health Surveillance: Revolutionizing Disease Detection and Epidemiological Research 10. Stochastic Forecasting Model: Spread of COVID-19 Virus as an Example 11. Impact of Environmental Reservoirs and Host Interactions on Mpox Transmission: A Deterministic Modeling Approach 12. Conclusion to AI and Data Science in Medical Research Topics

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Author Information

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.

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