AI and Data Science in Medical Research
- 1st Edition - November 1, 2025
- Imprint: Academic Press
- Editor: Olfa Boubaker
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 7 6 3 8 - 5
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 7 6 3 9 - 2
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 imagin… Read more
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Request a sales quoteAI 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.
- Emphasizes the integration of AI and data science into medical research, showcasing their influence on drug discovery, medical imaging, diagnostics, and genomic medicine
- Explores how AI accelerates therapeutic compound discovery and optimizes drug development pipelines, leading to advancements in medical imaging for early disease detection and neuroimaging
- Covers AI's application in genomic medicine, providing insights into personalized treatment strategies, and a discussion on AI's contribution to public health surveillance, focusing on disease detection and epidemiological research
Biomedical researchers and healthcare data scientists interested in applying AI and data science to drug discovery, medical imaging, genomic medicine, and public health surveillance
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
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
- Edition: 1
- Published: November 1, 2025
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780443276385
- eBook ISBN: 9780443276392
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Olfa Boubaker
Pr. Olfa Boubaker is a full professor at the National Institute of Applied Sciences and Technology (INSAT) at the University of Carthage, Tunisia, where she specializes in control theory, nonlinear systems, and robotics. She holds a Ph.D. in Electrical Engineering from the National Engineering School of Tunis and a Habilitation Universitaire in Control Engineering from the National Engineering School of Sfax. Professor Boubaker has led numerous research projects in sustainable development, including medical robotics and green energy. She has authored over 150 peer-reviewed papers and several books, and she is the founder/editor of the book series Medical Robots and Devices. Additionally, she serves as an associate editor for the journal Robotica and the International Journal of Advanced Robotic Systems, contributing to various scientific journals and mentoring numerous engineering graduates.
Affiliations and expertise
Full Professor, National Institute of Applied Sciences and Technology (INSAT), University of Carthage, Tunisia