Artificial Intelligence for Internet of Things (IoT) and Health Systems Operability (eBook, PDF)

AI for IoT and Health Systems
Redaktion: Souri, Alireza; Bendak, Salaheddine

• Format: PDF

Produktbeschreibung

IoTHIC-2023 is a multidisciplinary, peer-reviewed international conference on Internet of Things (IoT) and healthcare systems with Artificial Intelligence (AI) techniques such as data mining, machine learning, image processing, and meta-heuristic algorithms. The AI-based techniques are applied on many fields of healthcare systems, including predicting and detecting diseases in hospitals, clinics, smart health monitoring systems, surgery, medical services, and etc.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 191
• Erscheinungstermin: 31. Januar 2024
• Englisch
• ISBN-13: 9783031527876
• Artikelnr.: 69887151

Inhaltsangabe

Drug-Drug Interaction, Interaction Type And Resulting Severity Forecasting By Machine Learning-Based Approaches.- Hybrid Network Protocol Information Collection and Dissemination in IoT Healthcare.- CNN-Based Model for Skin Diseases Classification.- Using explainable artificial intelligence and knowledge graph to explain sentiment analysis of COVID-19 post on the Twitter.- An IoT-based Telemedicine System for the Rural People of Bangladesh.- Comparison of Predicting Regional Mortalities Using Machine Learning Models.- Benign and Malignant Cancer Prediction using Deep Learning and Generating Pathologist Diagnostic Report.- An Integrated Deep Learning Approach for Computer-Aided Diagnosis of Diverse Diabetic Retinopathy Grading.- Covid-19 Detection based on Chest X-ray images us-ing Attention Mechanism Modules and Weight Uncertainty in Bayesian Neural Networks.- A Stochastic Gradient Support Vector Optimization Algorithm for Predicting ChronicKidney Diseases.- Intelligent Information Systems in Healthcare sector: Review Study.- Design of a Blockchain-based Patient Record Tracking System.- IoT Networks and Online Image Processing in IMU-based Gait Analysis.- Reducing Patient Waiting Time in Ultrasonography Using Simulation and IoT Application