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

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K. P. Bindu Madavi,K. Krishna Sowjanyanships; (iii) task-based coordination; and (iv) information technology support, which together identified the needs of collaborative disaster response coordination. Using evidence from the data, these factors were related to one another to develop a framework for context-aware multi-party coordinati

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Aarti Sangwannships; (iii) task-based coordination; and (iv) information technology support, which together identified the needs of collaborative disaster response coordination. Using evidence from the data, these factors were related to one another to develop a framework for context-aware multi-party coordinati

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3004-958X rs overseeing this volume’s creation we take pride in presenting an assemblage of contributions that mirror the research findings, innovations and optimal practices in healthcare technology...Our aim is to enco978-3-031-65024-6978-3-031-65022-2Series ISSN 3004-958X Series E-ISSN 3004-9598

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Patient Health Services for Early Detection Therapy of Diabetes Mellitus with Expert System and IOTds accompanied by healing therapy and treatment methods. This system was created so that sufferers can understand and understand the types of diabetes mellitus along with healing therapies and how to treat them. This system provides several disease prevention solutions according to the type of disea

POINT

Integrating IoT and AI in Healthcare: A Novel MS-GNN Framework for Disease Diagnosis,“accuracy, sensitivity, specificity, and AUC (Area under the Curve)” for heart disease, diabetes, and thyroid datasets. Based on experimental results, the proposed approach attained 95.87, 95.36, and 90.45% accuracy on three different datasets. The results highlight the potential of AI and IoT in sm

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Advancing Glioblastoma Treatment Through AI-Driven Radiomics: A Comparative Study of Feature Selecteighbour, Quadratic Discriminant Analysis, and Multi-layer Perceptron, among others. The main objective is to identify the most powerful combinations that improve the capacity to forecast accurately and reliably, therefore making a significant contribution to the advancement of personalised medical

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Artificial Intelligence in Personalized Health Services for Better Patient Care,els. By taking into consideration the fact that each patient responds differently to treatments, this not only increases the efficacy of medical interventions but also reduces their negative consequences. The chapter also covers how artificial intelligence can expedite diagnostic procedures. Artific

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Machine Learning-Based Autism Spectrum Disorder Prediction: A Comparative Approach,s the efficacy of ML techniques in prediction of Autism Spectrum Disorder (ASD). Notably, the study finds that Random Forest and Extra Tree models exhibit high precision in test outcomes. This underscores the promising potential of ML methodologies in accurately predicting ASD. The research methodol

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Preventive Health Care System for Early Heart Disease Detection Using IoT and Machine Learning,icient in analyzing large volumes of data. A Preventive health care framework is proposed in this paper to predict early heart disease by procuring data such as Heart Rate (HT), Systolic Blood pressure (SBP), and Diastolic blood pressure (DBP) from wearable IoT Devices. The same data is analyzed usi