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Artificial intelligence for Internet of Things (IoT) and health systems operability = AI for IoT and health systems /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence for Internet of Things (IoT) and health systems operability/ edited by Alireza Souri, Salaheddine Bendak.
Reminder of title:	AI for IoT and health systems /
other author:	Souri, Alireza.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	x, 191 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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 Chronic Kidney 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.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence - Medical applications -
Online resource:	https://doi.org/10.1007/978-3-031-52787-6
ISBN:	9783031527876

Artificial intelligence for Internet of Things (IoT) and health systems operability = AI for IoT and health systems /
Artificial intelligence for Internet of Things (IoT) and health systems operabilityAI for IoT and health systems /[electronic resource] :edited by Alireza Souri, Salaheddine Bendak. - Cham :Springer Nature Switzerland :2024. - x, 191 p. :ill. (some col.), digital ;24 cm. - Engineering cyber-physical systems and critical infrastructures,82731-5010 ;. - Engineering cyber-physical systems and critical infrastructures ;8..

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 Chronic Kidney 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.

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.

ISBN: 9783031527876

Standard No.: 10.1007/978-3-031-52787-6doiSubjects--Topical Terms:

660945
Artificial intelligence
--Medical applications

LC Class. No.: R859.7.A78

Dewey Class. No.: 610.28563

Artificial intelligence for Internet of Things (IoT) and health systems operability = AI for IoT and health systems /
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520 $a 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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