Identifying Multiple Diseases in the Human Body using Machine Learning

The main causes of death in India and around the world are chronic illnesses like heart disease, diabetes, and Parkinson's disease. There is a need for potential treatments for chronic diseases because of its higher mortality rate than other diseases. The increase of medical data in healthcare...

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Bibliographic Details
Published in2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) pp. 872 - 877
Main Authors Nagaraj, P, Muneeswaran, V, Karthik Goud, B, Arjun, k, Vigneshwar Reddy, G, Girish Kumar Reddy, P
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.07.2023
Subjects
chronic diseases
Communication systems
diagnosis system
Heart
KNN
Machine learning
Machine learning algorithms
Medical treatment
prediction
Prediction algorithms
Predictive models
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Summary:The main causes of death in India and around the world are chronic illnesses like heart disease, diabetes, and Parkinson's disease. There is a need for potential treatments for chronic diseases because of its higher mortality rate than other diseases. The increase of medical data in healthcare domain and its accurate analysis are beneficial for early disease identification, patient treatment, and community services. Incorrect diagnosis increases the fatality. Thus, precise diagnosis tools for chronic diseases are required due to the high risk of diagnosis. Hence, to provide a promising solution with high accuracy, this study offers a unique diagnosis method based on machine learning. Several machine learning methods are being used in this study, and the algorithm for the prediction is chosen based on the model's accuracy. The proposed model performs disease prediction with an accuracy of 87.66%.
DOI:10.1109/ICESC57686.2023.10193060