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Disease Prediction Based on Symptoms Given by User Using Machine Learning

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Abstract

In recent times, many researchers have designed various automated analysis models using different supervised learning models. An early diagnosis of disease may control the death rate caused by those diseases. This project is concerned with a new way for recognition model; automated disease diagnosis model is intended using the machine learning models. Here we considered sample records of patients diagnosed with 41 different diseases for analysis, where 95 of 132 independent symptoms closely related to the selected diseases were chosen and are further optimized. In the proposed model, the data are listed into a Tkinter GUI; the analysis is then performed and predicts the disease. Decision tree and Naive Bayes algorithms are used for prognosis. The precise analysis of medical databases benefits the analysis of predicting the disease earlier that can help to provide better patient care and services.

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The authors declare that they have not received any funding.

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Correspondence to A. Divya.

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This article is part of the topical collection “Intelligent Systems” guest edited by Geetha Ganesan, Lalit Garg, Renu Dhir, Vijay Kumar, and Manik Sharma.

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Divya, A., Deepika, B., Durga Akhila, C.H. et al. Disease Prediction Based on Symptoms Given by User Using Machine Learning. SN COMPUT. SCI. 3, 504 (2022). https://doi.org/10.1007/s42979-022-01399-0

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