IoT Based Intelligent Computer-Aided Diagnosis and Decision Making System for Health Care

Chola, C.; Heyat, M. B. B.; Akhtar, F.; Al Shorman, O.; Bibal Benifa, J. V.; Muaad, A. Y. M.; Masadeh, M.; Alkahatni, F.

Pandemic Patient Health Monitoring Platform (PPHMP) with the help of the internet of things (IoT) and cloud computing is proposed in this paper. As a result of a pandemic such as a coronavirus outbreak, healthcare task needs a system includes a continuous diagnosis for monitoring patients and supports decision making. The system should be also helpful for healthcare providers. Moreover, it should be accurate and robust based on machine learning. The proposed PPHMP would be helpful in terms of its efficiency for remote patients who are not supposed to visit the hospital where the health monitoring task could be continuous. In our work, we proposed an algorithm to predict the current health status of patients accompanied by continuous monitoring connected with their healthcare providers. Patient's health is considered with other parameters and algorithms such as K- nearest neighbor, logistic regression, support vector machine, random forest and Adaboost Classifiers. Thus, we were able to provide a tool for assisting patients, physicians and the health care system, where such a decision-making system has an accuracy of 93%. © 2021 IEEE.