Hadi Kazemi-Arpanahi
Dept. of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran.
[ 1 ] - Comparison of Four Data Mining Algorithms for Predicting Colorectal Cancer Risk
Background and Objective: Colorectal cancer (CRC) is one of the most prevalent malignancies in the world. The early detection of CRC is not only a simple process, but it is also the key to its treatment. Given that data mining algorithms could be potentially useful in cancer prognosis, diagnosis, and treatment, the main focus of this study is to measure the performance of some data mining class...
[ 2 ] - Determination of the Most Important Diagnostic Criteria for COVID-19: A Step forward to Design an Intelligent Clinical Decision Support System
Background & Objective: Since the clinical and epidemiologic characteristics of coronavirus disease 2019 (COVID-19) is not well known yet, investigating its origin, etiology, diagnostic criteria, clinical manifestations, risk factors, treatments, and other related aspects is extremely important. In this situation, clinical experts face many uncertainties to make decision about COVID-19 progn...
[ 3 ] - Proposing an Intelligent Monitoring System for Early Prediction of Need for Intubation among COVID-19 Hospitalized Patients
Introduction: Predicting acute respiratory insufficiency due to coronavirus disease 2019 (COVID-19) can diminish the severe complications and mortality associated with the disease. This study aimed to develop an intelligent system based on machine learning (ML) models for frontline clinicians to effectively triage high-risk patients and prioritize who needs mechanical intubation (MI). Material...
Co-Authors