Abstract: We are designing a system called Disease Prediction using Machine Learning which is dedicated for medical sector. We see that there are many online diagnosis systems available but we can encounter one thing that this system has a search bar for searching the expertise on the basis of symptoms or diseases and guide to the user for nearby location of hospitals in the emergency situation. Many peoples are facing problems and challenges regarding disease and they are looking for online helps.
If this type of system is made for recommendation system used by doctors’ medicines it will beneficial for real time use of system. Now coming to technical things for the prediction of disease we are used four different algorithms namely Decision Tree Classifier, Random Forest, K-Nearest Neighbor, Naive Bayes Classifier.
All these algorithms are directly connected to tanning and testing dataset and GUI. Users of the system are layman so they are unable to use and understand this type of system so in future we are going to use some Human Interaction concepts in same project or system like local language can be added which is understandable by users of different regions. So as a software engineers we are developed a system called Disease Prediction using Machine Learning which takes five symptoms as an input and gives prediction of disease from which user is suffering.
We are also tried to use feedback system in our application to improve system accuracy, currently all algorithms give up to 94% of accuracy.
Keyword: Decision Tree Classifier, Random Forest, K-Nearest Neighbor, Naive Bayes Classifier
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DOI:
10.17148/IJARCCE.2022.111113
