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072 7 _aTEC059000
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245 1 0 _aRevolutionizing Healthcare 5.0: The Power of Generative AI
_h[electronic resource] :
_bAdvancements in Patient Care Through Generative AI Algorithms /
_cedited by Pronaya Bhattacharya, Haipeng Liu, Pushan Kumar Dutta, Joel J. P. C. Rodrigues, Gautam Sethi.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aIX, 476 p. 165 illus., 131 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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347 _atext file
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490 1 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v571
505 0 _aThe emerging healthcare landscape -- AI for Healthcare 5.0: A shift towards personalized healthcare -- Transition to Generative AI in Healthcare 5.0 -- Drug Synthesis through Generative AI Models -- Generative AI for Data Augmentation in Clinical Trials -- Generative AI models for Personalized Healthcare -- Generative Deep Models for Medical Imaging -- Generative AI-driven fitness and real-time healthcare monitoring and control -- The future of Surgery and Anatomical Operations via Generative AI -- Generative models for AR/VR assisted Healthcare 5.0 -- Accuracy and Reliability of Synthetic Data Generation.
520 _aThis book serves as a critical resource that bridges the gap between burgeoning technology and its practical implementation. The book starts with an in-depth exploration of healthcare 5.0 principles, laying the foundation for the reader to understand the current shifts in healthcare paradigms. Then, it dives into the intricacies of generative models in healthcare, detailing how these algorithms work and the applications they serve. The book further delves into the subsets of generative machine learning and deep learning techniques in healthcare. As we move towards more complex applications, the book takes a turn to address the critical subject of interpretability and explainability in generative models, a topic that resonates profoundly given the life-critical nature of medical decisions. Finally, the book concludes with a robust discussion on the security and privacy concerns that accompany the deployment of GAI in real healthcare settings. By offering a multidimensional viewpoint—coupled with case studies, statistical analyses, and expert insights—the book ensures that the reader is left with a nuanced understanding of how GAI can be both a boon and a challenge in healthcare. As such, the proposed book serves as an indispensable resource for healthcare professionals, data scientists, researchers, and anyone invested in the future of healthcare and AI.
650 0 _aBiomedical engineering.
650 0 _aComputational intelligence.
_964052
650 0 _aArtificial intelligence.
_958441
650 1 4 _aMedical and Health Technologies.
650 2 4 _aComputational Intelligence.
_964052
650 2 4 _aArtificial Intelligence.
_958441
700 1 _aBhattacharya, Pronaya.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
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700 1 _aLiu, Haipeng.
_eeditor.
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700 1 _aDutta, Pushan Kumar.
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_4http://id.loc.gov/vocabulary/relators/edt
_982769
700 1 _aRodrigues, Joel J. P. C.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
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700 1 _aSethi, Gautam.
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710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031757709
776 0 8 _iPrinted edition:
_z9783031757723
776 0 8 _iPrinted edition:
_z9783031757730
830 0 _aStudies in Systems, Decision and Control,
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856 4 0 _uhttps://doi.org/10.1007/978-3-031-75771-6
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