This book discusses current concepts and future translational possibilities of Artificial Intelligence (AI) in human healthcare and diseases. The initial chapter reviews the application and integration of AI and multi-omics to develop novel diagnostic and therapeutic strategies. The book chapter also explores the recent advances in data-driven approaches that aided state-of-the-art AI for biomarker discovery and better disease diagnosis. The book also offers computational and oncological prospects for the role of AI in radio genomics, as well as its offers, achievements, opportunities, and…mehr
This book discusses current concepts and future translational possibilities of Artificial Intelligence (AI) in human healthcare and diseases. The initial chapter reviews the application and integration of AI and multi-omics to develop novel diagnostic and therapeutic strategies. The book chapter also explores the recent advances in data-driven approaches that aided state-of-the-art AI for biomarker discovery and better disease diagnosis. The book also offers computational and oncological prospects for the role of AI in radio genomics, as well as its offers, achievements, opportunities, and limitations in the current clinical practices. The chapters further cover the role of the current state of AI in Cardiovascular Disease, Obesity and Diabetes, Neurological Diseases, and Infectious Diseases. Towards the end, the book highlights the use of AI in diverse pharmaceutical industry sectors, including drug discovery and development, drug repurposing, and improving pharmaceutical productivity. This book is handy for basic, translational, clinical & interdisciplinary researchers and bioinformaticians.
Dr. Muzafar A. Macha is a Ramalingaswami Fellow, Assistant Professor, and Head of the Watson-Crick Centre for Molecular Medicine at the Islamic University of Science and Technology (IUST), Kashmir, India. He holds a Master's in Biochemistry from Jamia Hamdard, New Delhi, where he was awarded a Gold Medal for academic excellence. He completed his Ph.D. in cancer biology at the All India Institute of Medical Sciences (AIIMS), New Delhi, focusing on Head and Neck Cancers (HNCs), for which he received the Gita Mittal Gold Medal for best basic cancer research. Dr. Macha conducted his postdoctoral research at the University of Nebraska Medical Center (UNMC), USA, in the Department of Biochemistry and Molecular Biology, where he later advanced to Assistant Professor. At UNMC, he led independent research programs focusing on deregulated signaling pathways and therapeutic targets in HNCs. He developed various in vitro cell lines and genetically engineered mouse models (GEMMs) for Head and Neck Squamous Cell Carcinoma (HNSCC), contributing significantly to translational cancer research. He has authored over 85 peer-reviewed articles and received several prestigious awards, including the Young Investigator Award, Scholar-in-Training Award, Educational Scholarship Award, and Best Performance Stipend Awards. The Government of India has honored him with the Ramalingaswami and Ramanujan Fellowships for his exceptional contributions to cancer research. Dr. Assif Assad is an Assistant Professor and Coordinator of the Centre for Artificial Intelligence at IUST. He holds a Bachelor's and Master's degree in Computer Applications from the University of Kashmir and a Ph.D. in Artificial Intelligence from IIT Roorkee. His doctoral work focused on the "Design and Applications of New Harmony Search Algorithms." His research spans Machine Learning, Deep Learning, Reinforcement Learning, and Nature-Inspired Optimization. He has applied AI technologies to medical imaging, drug design, satellite image analysis, precision agriculture, and bioinformatics. Dr. Assad has led 12 research projects funded by DST, ICMR, and the Higher Education Department, Government of India, amounting to several crores. He is also an inventor with 10 patents in areas like AI-driven plant disease detection, Pashmina authentication, paddy seed classification, and cancer subtype detection. As an educator, he has taught courses in AI, Machine Learning, Evolutionary Computing, Data Structures, Python, C Programming, DBMS, Parallel Programming (MPI), and more. He has organized numerous training programs and workshops, playing a vital role in fostering AI literacy and innovation. Dr. Muzafar Rasool Bhat is a Senior Assistant Professor at the Centre for Artificial Intelligence, Islamic University of Science and Technology (IUST). He earned his Ph.D. in Computer Science from the University of Kashmir in 2019, with a focus on probabilistic topic modeling and its applications in bioinformatics. Dr. Bhat’s research interests include Machine Learning and Deep Learning, with practical applications in Computer Vision, Artificial Intelligence for Human Health, and AI-driven solutions for agriculture. His interdisciplinary and collaborative approach has enabled impactful translational research, combining strong theoretical foundations with real-world problem-solving. He has been part of over a dozen funded research grants from premier Indian funding agencies such as DST, SERB, and ICMR, further underscoring the significance and applicability of his work. Over the years, Dr. Bhat has contributed to more than 40 peer-reviewed publications and holds several patents. His work applies AI to pressing challenges in human health and agriculture, demonstrating both innovation and societal relevance. In addition to his research, Dr. Bhat is actively involved in academic leadership and curriculum development and has played a pivotal role in nurturing AI-based research at IUST. His contributions continue to shape the academic and research landscape of the institution and beyond.
Inhaltsangabe
1. The Magic of Artificial Intelligence-1.- 2. Magic of Artificial Intelligence-2.- 3. Deep Reinforcement Learning in Medical Science: Methods, Applications, and Future Directions.- 4. The problem of Generialization and Explainability in deep learning algorithms.- 5. Artificial Intelligence and Omics in Health and Diseases.- 6. Artificial Intelligence in Biomarker Discovery and Disease Diagnosis.- 7. Artificial Intelligence in Biomarker Discovery and Disease Diagnosis-2.- 8. Radiogenomics and Artificial Intelligence in Health and Diseases.- 9. Artificial Intelligence and the Use of Imaging Modalities in Biomedical Sciences.- 10. Artificial Intelligence in Cardiovascular Diseases.- 11. Artificial Intelligence in Obesity and Diabetes.- 12. AI-Powered Revolution in Infectious Disease Management: From Early Diagnostics to Drug Discovery.- 13. Artificial Intelligence in Oncology.- 14. Artificial Intelligence in Precision Oncology, Genomic Medicine and Disease Monitoring.- 15. Artificial Intelligence in Drug Discovery and Drug Target Interactions.- 16. Artificial Intelligence and Cancer Immunotherapy.- 17. Deep Learning Based Techniques for Detection of Cancer.
1. The Magic of Artificial Intelligence-1.- 2. Magic of Artificial Intelligence-2.- 3. Deep Reinforcement Learning in Medical Science: Methods, Applications, and Future Directions.- 4. The problem of Generialization and Explainability in deep learning algorithms.- 5. Artificial Intelligence and Omics in Health and Diseases.- 6. Artificial Intelligence in Biomarker Discovery and Disease Diagnosis.- 7. Artificial Intelligence in Biomarker Discovery and Disease Diagnosis-2.- 8. Radiogenomics and Artificial Intelligence in Health and Diseases.- 9. Artificial Intelligence and the Use of Imaging Modalities in Biomedical Sciences.- 10. Artificial Intelligence in Cardiovascular Diseases.- 11. Artificial Intelligence in Obesity and Diabetes.- 12. AI-Powered Revolution in Infectious Disease Management: From Early Diagnostics to Drug Discovery.- 13. Artificial Intelligence in Oncology.- 14. Artificial Intelligence in Precision Oncology, Genomic Medicine and Disease Monitoring.- 15. Artificial Intelligence in Drug Discovery and Drug Target Interactions.- 16. Artificial Intelligence and Cancer Immunotherapy.- 17. Deep Learning Based Techniques for Detection of Cancer.
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