Applying Artificial Intelligence to Computational Biology and Medical Informatics
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Home > Mathematics and Science books > Biology, life sciences > Life sciences: general issues > Computational biology / bioinformatics > Applying Artificial Intelligence to Computational Biology and Medical Informatics
Applying Artificial Intelligence to Computational Biology and Medical Informatics

Applying Artificial Intelligence to Computational Biology and Medical Informatics


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About the Book

Applying Artificial Intelligence to Computational Biology and Medical Informatics explores the transformative role of AI and machine learning in modern biomedical research and healthcare. 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. Other sections address 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.

Table of Contents:
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

About the Author :
Mohammad Sufian Badar, PhD, is an Assistant Professor in the Department of Computer Science and Engineering, SEST, Jamia Hamdard, New Delhi. Previously, he was a Senior Teaching Faculty at UC Riverside, CA, USA, and an Analytics Architect at CenturyLink in Denver, CO, USA. He holds an MS in Molecular Science and Nanotechnology and a PhD in Engineering from Louisiana Tech University. He earned an MSc in Bioinformatics from Jamia Millia Islamia, New Delhi. With many years of teaching, research, and industry experience, Dr. Badar has published in conferences and journals, authored chapters on AI, machine learning, blockchain, IoT, and computational biology and has edited and authored several books in his area of interest like AI, ML, computational biology, and the integration of AI/ ML with health sciences.



Product Details
  • ISBN-13: 9780443449154
  • Publisher: Elsevier Science Publishing Co Inc
  • Publisher Imprint: Academic Press Inc
  • Height: 235 mm
  • No of Pages: 220
  • Weight: 450 gr
  • ISBN-10: 0443449155
  • Publisher Date: 01 Sep 2026
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Width: 191 mm


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