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010   $a3-031-08637-6
024 7 $a10.1007/978-3-031-08637-3
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035   $a(DE-He213)978-3-031-08637-3
035   $a(PPN)272264296
035   $a(EXLCZ)9927240592300041
100   $a20230626d2023      u|         0
101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aInterpretable Cognitive Internet of Things for Healthcare /$fedited by Utku Kose, Deepak Gupta, Ashish Khanna, Joel J. P. C. Rodrigues
205   $a1st ed. 2023.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023.
215   $a1 online resource (203 pages)
225 1 $aInternet of Things, Technology, Communications and Computing,$x2199-1081
311   $a9783031086366 
327   $aIntroduction -- Essentials of Cognitive IoT for Healthcare -- Interpretability Problem in IoT for Healthcare -- Transparent and Black-Box IoT Systems for Healthcare -- Evaluation of Cognitive Capabilities of IoT in Healthcare -- Massive Health Data Analytics for Cognitive IoT -- Usability Evaluation of Cognitive IoT for Healthcare -- Hybrid Methods for Interpretable IoT for Healthcare -- Interpretable Cognitive IoT for Pandemics -- Interpretable Cognitive IoT for Cancer -- Interpretable Cognitive IoT for Sustainable Massive Health -- Interpretable Cognitive IoT for Health Robotics -- Interpretable Cognitive IoT for Personal Healthcare -- Wearables in the Context of IoT for Massive Healthcare -- Security for Massive Health Data Used by Cognitive IoT -- Future Insights for Interpretable Cognitive IoT in Healthcare -- Conclusion.
330   $aThis book presents research on how interpretable cognitive IoT can work to help with the massive amount of data in the healthcare industry. The authors give importance to IoT systems with intense machine learning features; this ensures the scope corresponds to use of cognitive IoT for understanding, reasoning, and learning from medical data. The authors discuss the interpretability of an intelligent system and its trustworthiness as a smart tool in the context of massive healthcare applications. As a whole, book combines three important topics: massive data, cognitive IoT, and interpretability. Topics include health data analytics for cognitive IoT, usability evaluation of cognitive IoT for healthcare, interpretable cognitive IoT for health robotics, and wearables in the context of IoT for healthcare. The book acts as a useful reference work for a wide audience including academicians, scientists, students, and professionals. Presents research and application of cognitive interpretable data for healthcare; Includes both positive outcomes and negative results of ongoing research into IoT and healthcare; Encourages readers to submit their data or open source software, to create a repository for ongoing study.
410  0$aInternet of Things, Technology, Communications and Computing,$x2199-1081
606   $aTelecommunication
606   $aBiomedical engineering
606   $aMedical informatics
606   $aCommunications Engineering, Networks
606   $aBiomedical Engineering and Bioengineering
606   $aHealth Informatics
615  0$aTelecommunication.
615  0$aBiomedical engineering.
615  0$aMedical informatics.
615 14$aCommunications Engineering, Networks.
615 24$aBiomedical Engineering and Bioengineering.
615 24$aHealth Informatics.
676   $a610.28546
676   $a610.28546
700   $aKose$b Utku$01076791
701   $aGupta$b Deepak$cPh.D.$01373631
701   $aKhanna$b Ashish$01076759
701   $aRodrigues$b Joel J. P. C$01373632
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910734871703321
996   $aInterpretable Cognitive Internet of Things for Healthcare$93404720
997   $aUNINA