An analysis of ML-based multiple disease prediction system
Author(s):
Abhishek Madhukar Gawade
Keywords:
multiple disease prediction, disease prediction, healthcare, data mining, machine learning.
Abstract
In recent years, people face various diseases because of environmental changes and their lifestyles. As a result, predicting diseases at an earlier stage becomes an important responsible task. However, reliable diagnosis based on symptoms was challenging for doctors, and the most difficult challenge is to accurately predict the disease. To overcome such problem data mining plays a significant role to predict the disease. There are many existing machine learning models available for healthcare analysis that will be focusing on a single disease at a time, like one for diabetes analysis, and one for heart disease like that. There is no single standard system where one analysis can perform more than one disease prediction based on symptoms and some other parameters like insulin level, blood pressure, etc. In this proposed project, a single standard disease prediction system is proposed which will analyze multiple diseases at a time. This project aims to detection of trends and the prevention of disease transmission, by using predictive analytics in healthcare which will enhance healthcare quality and reduces the burden on doctors. This research paper was carried out to analyze the relevant attributes, factors, and most efficient algorithms among different algorithms used in disease prediction.
Article Details
Unique Paper ID: 157282

Publication Volume & Issue: Volume 9, Issue 6

Page(s): 540 - 548
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