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Integrating Artificial Intelligence and IoT for Advanced Health Informatics [electronic resource] : AI in the Healthcare Sector / edited by Carmela Comito, Agostino Forestiero, Ester Zumpano.

Contributor(s): Material type: TextTextLanguage: İngilizce Series: Internet of Things, Technology, Communications and ComputingPublisher: Cham : Springer International Publishing : Imprint: Springer, 2022Edition: 1st ed. 2022Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783030911812
Subject(s): NLM classification:
  • W 26.55.A7
Online resources:
Contents:
1. Lower-Gait Tracking Application Using Smartphones and Tablets -- 2. One-class classification approach in accelerometer based remote monitoring of physical activities for healthcare applications -- 3. Detecting and monitoring behavioural patterns in individuals with cognitive disorders in the home environment with partial annotations -- 4. Towards On-device Weight Monitoring from Selfie Face Images Using Smartphones -- 5. Convergence between IoT and AI for Smart Health and Predictive Medicine -- 6. An Artificial Intelligence and Internet of Things Platform for Healthcare and Industrial Applications -- 7. Methods in Digital Mental Health: Smartphone-based Assessment and Intervention for Stress, Anxiety and Depression -- 8. AI for the detection of the Diabetic Retinopathy -- 9. Enhancing EEG-based Emotion Recognition with Fast Online Instance Transfer -- 10. Using Association Rules to mine Actionable Knowledge from Internet of Medical Thinks data.
Summary: The book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare. The authors discuss efficient means to collect, monitor, control, optimize, model, and predict healthcare data using AI and IoT. The book presents the many advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. AI techniques are presented that play a crucial role in dealing with large amounts of heterogeneous, multi-scale and multi-modal data coming from IoT infrastructures. The book is intended to cover how the fusion of IoT and AI allows the design of models, methodologies, algorithms, evaluation benchmarks, and tools can address challenging problems related to health informatics, healthcare, and wellbeing.
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Holdings
Item type Current library Home library Collection Call number Copy number Status Notes Date due Barcode
E-Book E-Book Tıp Fakültesi Medikal Kütüphane Tıp Fakültesi Medikal Kütüphane E-Kitap Koleksiyonu W 26.55.A7EBK (Browse shelf(Opens below)) 1 Geçerli değil-e-Kitap / Not applicable-e-Book EBK03171

1. Lower-Gait Tracking Application Using Smartphones and Tablets -- 2. One-class classification approach in accelerometer based remote monitoring of physical activities for healthcare applications -- 3. Detecting and monitoring behavioural patterns in individuals with cognitive disorders in the home environment with partial annotations -- 4. Towards On-device Weight Monitoring from Selfie Face Images Using Smartphones -- 5. Convergence between IoT and AI for Smart Health and Predictive Medicine -- 6. An Artificial Intelligence and Internet of Things Platform for Healthcare and Industrial Applications -- 7. Methods in Digital Mental Health: Smartphone-based Assessment and Intervention for Stress, Anxiety and Depression -- 8. AI for the detection of the Diabetic Retinopathy -- 9. Enhancing EEG-based Emotion Recognition with Fast Online Instance Transfer -- 10. Using Association Rules to mine Actionable Knowledge from Internet of Medical Thinks data.

The book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare. The authors discuss efficient means to collect, monitor, control, optimize, model, and predict healthcare data using AI and IoT. The book presents the many advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. AI techniques are presented that play a crucial role in dealing with large amounts of heterogeneous, multi-scale and multi-modal data coming from IoT infrastructures. The book is intended to cover how the fusion of IoT and AI allows the design of models, methodologies, algorithms, evaluation benchmarks, and tools can address challenging problems related to health informatics, healthcare, and wellbeing.

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