Designing of Multiple Disease Prediction Model by using Machine Learning and Spyder API

Abstract

Abstract: Many of the existing machine learning models for health care analysis are concentrating on one disease per analysis. Like one analysis is for diabetes, one for cancer, one for skin diseases like that. There is no common system where one analysis can perform more than one disease prediction. In case of doctor is not available we can use this model. In this model we are proposing a system which used to predict multiple diseases by using Spyder API. In this model we used to analyse Diabetes prediction, Heart disease prediction and parkinson’s disease prediction analysis. We also developed a model in extension with that based on symptoms it can predict the diseases. To implement multiple disease analysis used machine learning algorithms, streamlit and Spyder API. Python pickling is used to save the model behaviour and python unpickling is used to load the pickle file whenever required. The importance of this model analysis in while analysing the diseases all the parameters which causes the disease is included so it possible to detect the maximum effects which the disease will cause. For example for diabetes analysis in many existing systems considered few parameters like age, sex, bmi, insulin, glucose, blood pressure and pregnancies are considered.