Applying Artificial Intelligence to Computational Biology and Medical Informatics

Häftad, Engelska, 2026

1 690 kr

Kommande

Beskrivning

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.

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 academic curricula

Produktinformation

Utgivningsdatum:2026-09-01
Mått:191 x 235 x undefined mm
Vikt:450 g
Format:Häftad
Språk:Engelska
Antal sidor:220
Förlag:Elsevier Science
ISBN:9780443449154

Utforska kategorier

Biologi inom Naturvetenskap och teknik

Mer om författaren

Mohammad “Sufian Badar, PhD is currently working as an Professor (Assistant) in the Department of Computer Science and Engineering, School of Engineering Sciences and Technology (SEST), Jamia Hamdard, New Delhi, India. Prior to that, he served as a Senior Teaching Faculty in the Department of Bioengineering at the University of California, Riverside, CA, USA. He served as an Analytics Architect in CenturyLink for more than a year in Denver, CO, USA. He possesses an excellent academic record with an MS degree in Molecular Science and Nanotechnology and a Ph.D. in Engineering from Louisiana Tech University Ruston, LA, USA, respectively. Before joining the Ph.D. program at Louisiana Tech University, he graduated with an MSc in Bioinformatics from Jamia Millia Islamia University, New Delhi, India. Dr. Sufian has over 18 years of teaching, research, and industry experience. He has published his research in conferences and highly reputed international journals. He has authored many chapters in the areas of Artificial Intelligence/Machine Learning and Blockchain/IoT. He has published six books with Elsevier, Springer Nature and Bentham, respectively. He recently submitted three book proposals with different publishers.He is currently in the process of developing a device that, using Biosensors, can correlate the physiology of the human body with the emotion recognition algorithm, giving us a clear measure of the amount of stress hormones in the body. Currently, he and his group have developed an ML model that predicts COVID-19 infection based on symptoms only, and we are now working on increasing the accuracy of our model.

Innehållsförteckning

1. Introduction to AI/ML, Computational Biology, and Medical Informatics2. AI/ML Applications in Medical Imaging3. Natural Language Technologies in Biomedical Domain4. AI/ML in Chemoinformatics5. Deep Learning Methods for Network Biology6. Probabilistic Optimization of ML for Heart Disease Prediction7. The Need for Interpretable and Explainable Deep Learning Data in Health Care8. Using hybrid models in healthcare data9. Improving Disease Prediction by Integrating Multiple ML and Optimization Techniques10. Ethical, Societal, and Legal Issues in AI/ML for Healthcare11. Deep Learning in Gait Abnormality Detection: Principles and Illustrations12. Broad Applications of Network Embedding in Computational Biology, Genomics, Medicine, and Health13. AI Use in Clinical Prediction14. AI/ML for Medical Informatics and Public Health15. AI in Medical Imaging for Developing Countries: Challenges and Opportunities16. AI Applications in Disease Diagnosis and Treatment: New Applications