Multi-disease prediction with machine learning
Keywords:
machine learning, disease prediction, random forest, naive bayes, support vector machineAbstract
In the present era, Machine learning (ML) algorithms are extensively used in computer assisted diagnosis of the disease based on the symptoms of the disease. The widespread use of healthcare applications in the pandemic time, provides a motivation to further develop new computer assisted diagnostic application in the healthcare domain. Prevention and treatment of disease, accurate and timely diagnosis of any health-related problem is essential. In the case of a serious illness, a standard diagnostic method may not be enough. We have proposed a system for predicting the disease. There were about forty-one diseases in the data corpus that needed to be analyzed based on the symptoms. The system delivers a disease prediction that a person may have depending on the symptoms. This diagnostic program can assist a physician in diagnosing disease, allowing for timely treatment and saving lives. The disease forecasting system was developed using ML models such as the Random Forests, the Naive Bayes, and the Support Vector Machine Classification Algorithm. The presented work outlines an analysis of the aforementioned algorithms.
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