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.

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. .