Applying Artificial Intelligence to Computational Biology and Medical Informatics

Mohammad Sufian Badar

• Publisher: Academic Press
• Year: 2026
• Topic: Biological Sciences
• eBook ISBN:
  9780443449161
• Subtopic: Biology
• Index: Biological Sciences

Applying Artificial Intelligence to Computational Biology and Medical Informatics explores the transformative role of AI and machine learning in modern biomedical research and healthcare. This volume bridges the gap between computational methods and biological applications, offering a comprehensive introduction for students and researchers across disciplines.The book covers foundational concepts in AI/ML, computational biology, and medical informatics, followed by in-depth chapters on medical imaging, network biology, chemoinformatics, and public health. It also addresses ethical and societal implications, interpretable AI, and real-world case studies, making complex topics accessible through clear language and structured content.Designed for early career researchers, students, and professionals without prior expertise in computer science or health sciences, this book provides a progressive learning path from basic to intermediate levels. Readers benefit from practical examples, online resources, and a coherent chapter structure that supports both academic study and applied research. - Introduces foundational concepts in AI, machine learning, computational biology, and medical informatics, enabling readers from diverse academic backgrounds to build a solid interdisciplinary understanding - Presents real-world case studies and practical applications of AI/ML in disease diagnosis, treatment, and public health, fostering translational insights and research relevance - Maintains a coherent pedagogical structure that progresses from basic to intermediate levels, supporting both self-paced learning and integration into academia curricula

Table of contents

• Title of Book
• 1. Introduction to AI/ML, computational biology, and medical informatics
• 2. AI/ML applications in medical imaging
• 3. Natural language technologies in biomedical domain
• 4. AI/ML in chemoinformatics
• 5. Deep learning methods for network biology
• 6. Probabilistic optimization of ML for heart disease prediction
• 7. The need for interpretable and explainable deep learning data in health care
• 8. Using hybrid models in healthcare data
• 9. Improving disease prediction by integrating multiple ML and optimization techniques
• 10. Ethical, societal, and legal issues in AI/ML for healthcare
• 11. Deep learning in gait abnormality detection: Principles and illustrations
• 12. Broad applications of network embedding in computational biology, genomics, medicine, and health
• 13. AI use in clinical prediction
• 14. AI/ML for medical informatics and public health
• 15. AI in medical imaging for developing countries: Challenges and opportunities
• 16. AI applications in disease diagnosis and treatment: New applications
• Index