Common human diseases prediction using machine learning based on survey data

Jabir Al Nahian (Daffodil International University)
Abu Kaisar Mohammad Masum (Daffodil International University)
Sheikh Abujar (Florida Institute of Technology)
Md. Jueal Mia (Daffodil International University)

Bulletin of Electrical Engineering and Informatics
Vol 11, No 6: December 2022

In this era, the moment has arrived to move away from disease as the primary emphasis of medical treatment. Although impressive, the multiple techniques that have been developed to detect the diseases. In this time, there are some types of diseases COVID-19, normal flue, migraine, lung disease, heart disease, kidney disease, diabetics, stomach disease, gastric, bone disease, autism are the very common diseases. In this analysis, we analyze disease symptoms and have done disease predictions based on their symptoms. We studied a range of symptoms and took a survey from people in order to complete the task. Several classification algorithms have been employed to train the model. Furthermore, performance evaluation matrices are used to measure the model's performance. Finally, we discovered that the part classifier surpasses the others.