Machine Learning-Based Skin And Heart Disease Diagnose Mobile App

Abstract

This research aims to develop a Mobile app for predicting major diseases we have to face nowadays. These days the heart disease is the main source of death around the world. It is a complex task to predict a heart attack with a doctor because more experience and knowledge are needed. Sometimes it may be gastritis or asthma symptoms. Also, the following most common disease is a skin disease. Most people have some skin disease, and they don’t even have time to check it from a medical centre. These diseases led to deadly cancers kind of things. Implementing the Smart health care application, the skin disease classification and treatment, and the heart disease predictions can be made domestically. The application is taken images of skin disease through the device camera. It classifies the disease with the Keras ResNet trained to classify the accuracy as eighty-seven point eighty-three as a percentage. The heart disease prediction module takes 14 different attributes that can access by the personal and predict the heart disease probability with the model of sklearn KNeighborsClassifier is trained as a percentage with an accuracy of eighty-three point nine. The application was developed on top of the android platform with the SQL Lite database integration.