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Titlebook: Revolutionizing Healthcare: AI Integration with IoT for Enhanced Patient Outcomes; Shashi Kant Gupta,Dimitrios A. Karras,Rajesh Natar Book

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樓主: energy
51#
發(fā)表于 2025-3-30 10:23:23 | 只看該作者
Transforming Healthcare: The Synergistic Fusion of AI and IoT for Intelligent, Personalized Well-Betunities to enhance patient care, improve diagnostic accuracy, and optimize operational efficiency. AI contributes to diagnostic precision through image analysis, predictive analytics, and personalized medicine, while IoT facilitates real-time data collection through wearable devices, remote patient
52#
發(fā)表于 2025-3-30 14:14:27 | 只看該作者
Machine Learning-Based Autism Spectrum Disorder Prediction: A Comparative Approach,opments in machine learning (ML) offer an exciting chance to enhance ASD prediction, transforming the diagnostic and management processes. This research paper implements an exhaustive examination of ML-based ASD prediction methods, emphasizing a comparative assessment of various ML algorithms and fe
53#
發(fā)表于 2025-3-30 16:52:32 | 只看該作者
54#
發(fā)表于 2025-3-30 20:55:18 | 只看該作者
Preventive Health Care System for Early Heart Disease Detection Using IoT and Machine Learning, regularly thereby preventing the disease from developing further. Continuous monitoring of the patient‘s condition is carried out effectively by using the technology of Sensor/IoT Devices. IoT devices for health care come under the emerging technology Internet of Medical Things (IoMT). The IoMT usa
55#
發(fā)表于 2025-3-31 02:08:01 | 只看該作者
56#
發(fā)表于 2025-3-31 06:34:01 | 只看該作者
AI Innovations in Health Care: Reshaping Diagnostics and Care,is of the various ways in which AI is transforming the industry, particularly in regards to their role in transforming diagnostic and care methods. AI technologies have brought about a new era, drastically changing the way that various allied health sector’s function. This chapter delves into the ke
57#
發(fā)表于 2025-3-31 11:22:21 | 只看該作者
58#
發(fā)表于 2025-3-31 14:12:56 | 只看該作者
An Approach to Pattern Prediction and Early Recognition of Lung Cancer Employing Machine Learning Ted diagnosis. By creating and implementing a novel machine learning architecture intended for early lung cancer diagnosis, our work aims to address this problem. To do this, an extensive dataset including a broad spectrum of health-related attributes is utilised. These include age, gender, lifestyle
59#
發(fā)表于 2025-3-31 20:52:55 | 只看該作者
60#
發(fā)表于 2025-3-31 23:50:39 | 只看該作者
Pixels, Perspectives, and Psychological Strain: Unravelling the Link Between Negative Body Image, In social and work adjustment. Leveraging a combination of traditional survey methods and cutting-edge IoT technologies, the research provides a nuanced understanding of the complexities surrounding body image perceptions. The findings reveal a consistent trend of females experiencing higher levels o
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