Full Description
AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice examines the transformative role of AI and data science in improving diagnosis, treatment, and healthcare delivery. It shows how machine learning, deep learning, and advanced signal and image analysis enable breakthroughs in genomics, multi-omics integration, biomedical imaging, EEG-based seizure prediction, and real-time physiological monitoring. The book highlights AI-driven stratification of complex syndromes such as sepsis, stroke, and acute respiratory distress syndrome, demonstrating how data-driven models support early detection, personalized interventions, and actionable clinical decisions.
The volume also presents system-level innovations, including AI-based forecasting for dialysis, blood supply management, and telemedicine optimization. It addresses ethical and regulatory challenges, fairness, transparency, data governance, and clinical validation, providing a practical roadmap for healthcare professionals, engineers, researchers, and policymakers. By integrating responsible, human-centered AI into precision medicine, the book illustrates clear pathways to enhance patient care, improve outcomes, and promote equitable healthcare.
Contents
Introduction to AI and Data Science in Precision Medicine, Predictive Analytics and Clinical Applications
Part I: Foundations of AI, Data Science, and Medical Training in Precision Medicine
1. Artificial Intelligence-Driven Personalized Medicine
2. AI Revolution in Healthcare: Enhancing Patient Care and Outcomes through Innovative Applications and Future Prospects
3. Precision medicine, omics, and treatable traits as a paradigm shift towards promising medical curriculum
Part II: Core Perspectives on AI in Precision Medicine: Genomics, Imaging, and Drug Discovery
4. Distributed Deep Learning Approaches for Genomics Analysis: A Comprehensive Review
5. Drug Discovery and Development: Leveraging AI and data science to accelerate the discovery of novel therapeutic compounds and optimize drug development pipelines
6. Advancements in Medical Imaging: Harnessing AI for Early Disease Detection and Diagnosis
Part III: Data-Driven AI Techniques for Diagnosis, Prediction, and Personalized Treatment
7. AI-Based Seizure Prediction Using EEG Signal to Image Conversion Techniques
8. CNN-Based Retinal Disease Classification Using OCT Imaging and EfficientNetB09. ML-based Prognostic models for hypertensive acute response for stroke patients in intensive care units and emergency departments
10. Precision Medicine in Acute Respiratory Distress Syndrome (ARDS)
11. Sepsis and precision medicine: Tailoring interventions using patient-specific data and biomarkers
Part IV: AI-Driven Optimization of Healthcare Systems and Medical Logistics
12. Enhancing Telemedicine and Remote Patient Monitoring with AI and Data Science
13. Enhancing Peritoneal Dialysis Care: Leveraging Predictive Analytics and AI
14. AI-Driven Blood Supply Chain Management: A Reinforcement Learning Approach
Part V: Emerging Trends, Ethical Challenges, and Future Perspectives in AI-driven Healthcare
15. Chaos Theory in AI-Driven Healthcare Systems: Unraveling Complex Data Patterns
16. Ethical Challenges of Artificial Intelligence in Critical Care
17. Data-Driven Decision-Making in Healthcare: Unlocking Value through Web Analytics
18. Implementing Responsible Artificial Intelligence-driven Precision Medicine in Critical Care
19. Enrichment Strategies in Precision Medicine for Future Clinical Trials
20. Conclusions in Precision Médecine and Predictive Analytics
