Technological Fusion in Experimental Medicine and Biology

Dr. Shubham Mahajan is an academic and researcher, member of IEEE, ACM, and IAENG. He earned a B.Tech from Baba Ghulam Shah Badshah University, an M.Tech from Chandigarh University, and a PhD from Shri Mata Vaishno Devi University. He is currently Assistant Professor at Amity University, Haryana, India. His research spans artificial intelligence and image processing, including video compression, image segmentation, fuzzy entropy, nature-inspired optimization, data mining, machine learning, robotics, and optical communications. He holds patents internationally and has published widely in high-impact venues; he has edited several Scopus-indexed books. He has received multiple awards for research excellence and travel support from IEEE, among others. He has served as IEEE Campus Ambassador at premier institutes and promotes international collaborations. He participates in technical program committees and editorial boards for conferences and journals, shaping discourse in AI and image processing.Dr. Kamal Upreti is an Associate Professor of Computer Science at CHRIST (Deemed to be University), Ghaziabad. He holds , a Ph.D. in Computer Science & Engineering, and a postdoctoral fellowship at National Taipei University of Business, Taiwan, funded by MHRD.With teaching, research, and industry exposure, he has produced numerous patents and publications. His interests span modern physics, data analytics, cybersecurity, ML, healthcare, embedded systems, and cloud computing. Notable projects include Hydrastore in Japan, IPDS in India, and an ICMR-funded cardiovascular-prediction project with GB Pant and AIIMS Delhi. Dr. Upreti serves as session chair, keynote speaker, trainer, and faculty developer, and has been honored as Best Teacher, Best Researcher, and an M.Tech Gold Medalist.

• Part I: Foundations of Experimental Medicine and Biology1. The Evolution of Experimental Medicine: From Bench Science to Human-Centered Innovation2. Human Biology in the Era of Technological Convergence: Integrating Artificial Intelligence, Nanotechnology, and Systems Biology for Next-Generation Healthcare3. Interdisciplinary Integration in Biomedical Research: Convergence of Artificial Intelligence, Engineering, and Clinical Sciences for Translational Innovation4. Ethical and Regulatory Landscapes in Technology-Driven Human Research: An Integrated Framework for AI-Enabled Healthcare SystemsPart II: Core Technologies Transforming Human Experimental Medicine5. Artificial Intelligence and Machine Learning in Biomedical Discovery: A Hybrid Review and Explainable Deep Learning Framework for Breast Cancer Detection6. Omics Revolution in Human Research: Bridging Multi-Omics Integration and Machine Learning for Precision Medicine7. Nanotechnology and Biomaterials in Experimental Medicine: A Machine Learning-Based Comparative Analysis for Nanoparticle Toxicity Prediction8. Advanced Imaging and Biosensing Technologies for Human Biology: AI-Assisted Pneumonia Detection and Intelligent Healthcare Applications9. AI-Assisted Organ-on-a-Chip Platforms for Precision Drug Screening and Translational MedicinePart III: Translational Integration Across the Research Workflow10. Cloud-scBioAge: Autoencoder-Based Single-Cell Transcriptomic Big-Data Modelling for Immune Aging Prediction and Biomarker Discovery11. Precision-CDSS: An Explainable AI-Based Framework for Therapy Response Prediction, Patient Stratification, and Clinical Decision Support in Precision Medicine12. Digital Twins and Simulation Models in Experimental Medicine13. Integrating Robotics, Automation, and Smart Devices in Experimental WorkflowsPart IV: Future Horizons in Human-Centered Biomedical Innovation14. Human–Technology Symbiosis: Co-evolution of Biology and Digital Tools15. Global Perspectives: Collaborative Networks in Experimental Medicine and Biology16. The Future of Technological Fusion in Experimental Medicine: Emerging Directions, Grand Challenges, and Strategic Roadmaps for Human-Centered Biomedical Innovation

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