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Produktbild: Resilient AI for Healthcare 5.0
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Resilient AI for Healthcare 5.0 Privacy, Ethics, and Trust

Aus der Reihe Cognitive Technologies

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

24.02.2027

Abbildungen

VI, 375 p. 113 illus., 96 illus. in color.

Herausgeber

Bipin Kumar Rai + weitere

Verlag

Springer

Seitenzahl

375

Maße (B/H)

15,5/23,5 cm

Sprache

Englisch

ISBN

978-3-032-42021-3

Beschreibung

Portrait

Dr. Bipin Kumar Rai is a Professor in the Department of Computer Science & Engineering, at Dayananda Sagar University, India. He holds a PostDoc from NKUST Taiwan, PhD from Banasthali Vidyapith, along with M.Tech and B.Tech degrees in Computer Science and Engineering. Dr. Rai has over 21 years of teaching experience at renowned institutions. His areas of interest include cryptography and information security, machine learning, and blockchain technology. He has published over 70 research papers in WoS/Scopus-indexed journals, conferences, and book chapters.

Dr. Rai has held various administrative roles, including Dean of Academics and Head of Department for NBA-accredited program. He has expertise in implementing Outcome-Based Education (OBE), which is essential for NBA/NAAC accreditation processes. Dr. Rai is actively engaged in professional development and is an esteemed member of professional bodies such as the Senior Member of IEEE, Computer Society of India (CSI), Indian Society for Technical Education (ISTE), and Association for Computing Machinery (ACM).

Dr. Rupa Rani is an Assistant Professor in the Department of CSE at Ajay Kumar Garg Engineering College, Ghaziabad, India, and is currently pursuing her Postdoctoral research under Prof. (Dr.) Chin-Shiuh Shieh at National Kaohsiung University of Science and Technology, Taiwan. She holds a Ph.D. in Computer Science & Engineering from Banasthali Vidyapith, Rajasthan.

Dr. Sushil Kumar Singh is an Associate Professor in the Department of Computer Engineering at Marwadi University, Rajkot, Gujarat, India. He has completed a PostDoc at London Metropolitan University, London, United Kingdom, under the supervision of Professor Bal Virdee. He received a Ph.D. degree from Seoul National University of Science and Technology, Seoul, South Korea, under the supervision of Professor Jong Hyuk Park. He received an M.Tech. Degree in Computer Science and Engineering from Uttarakhand Technical University, Dehradun, India. He also received an M.E. degree in Information Technology from Karnataka State University, Mysore, India. He has also been the lab leader of the UCS Lab at the Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, South Korea. He has received the Best Lab Leadership Award from UCS Lab for 2019-2021. He is selected in the Top 2% of scientists for the 2022-2023, 2023-2024, and 2024-2025 years as per the list compiled by Stanford University and published by Elsevier. He has more than 15 years of experience teaching in the field of computer science.

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

24.02.2027

Abbildungen

VI, 375 p. 113 illus., 96 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

375

Maße (B/H)

15,5/23,5 cm

Sprache

Englisch

ISBN

978-3-032-42021-3

Herstelleradresse

Springer Nature Customer Service Center GmbH
Europaplatz 3
69115 Heidelberg
DE
ProductSafety@springernature.com

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  • Produktbild: Resilient AI for Healthcare 5.0
  • .- Evolution of Healthcare 5.0.

    .- Core Principles of Resilient Artificial Intelligence in Healthcare Systems.

    .- Privacy Fundamentals, Patient Rights, and Threat Landscapes in Health AI.

    .- Advanced Privacy-Preserving Technologies in Collaborative Healthcare AI.

    .- Cyber security and Threat Mitigation for Healthcare AI Systems.

    .- Ethical AI Frameworks for Responsible Healthcare Decision-Making.

    .- Bias Detection, Fairness Auditing in Medical AI Models.

    .- Explainable AI Techniques.

    .- Informed Consent and Patient Engagement in the AI-Driven Healthcare Era.

    .- Explainable and Interpretable AI Techniques for Clinical Trust.

    .- Human–AI Collaboration and Interaction Models in Clinical Practice.

    .- Resilience Against Model Drift, Data Shifts, and Performance Degradation.

    .- Case Studies on Resilient AI in Clinical Diagnostics and Decision Support.

    .- Resilient AI Applications in Telemedicine, Wearables, and Remote Care.

    .- Future Trajectories, Governance, and Sustainable Adoption of Healthcare AI.