Analysis of Disease and Risk Prediction using ML

Authors

  • Megha Gupta
  • Ruchika Gupta

Abstract

This paper comprises of efficient machine learning algorithms used in predicting diseases through symptoms. As, the health industry has a huge amount of data for various fields, so we want to make a system where we can use various other applications of machine learning on health industry. This all had been done to make better medical decisions and also for rise in the accuracy. As an accurate analysis and early prediction of disease helps in the patient care and the society services. These all challenges can be easier with the help of various tools, algorithms, and framework provided by the machine learning. In addition to all these predictions, we are making a chatbot for all that where patients can add the symptoms that are helpful to predict the disease and also check the risk of heart disease status through the various information provided to system by the patients and the database is obtained from UCI Repository.

Keywords: Decision tree classification, logistic regression, Naive Bayes, NLTK, risk prediction

Cite this Article: Megha Gupta, Ruchika Gupta. Analysis of Disease and Risk Prediction using ML. Journal of Multimedia Technology & Recent Advancements. 2020; 7(1): 7–13p.

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Published

2020-06-02

Issue

Vol. 7 No. 1 (2020)

Section

Research Articles

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