Computerized Healthcare System Embedded with Machine Learning


Authors : Amal S, Athira Lagi, Thomas Kuruvilla, Leya Elizabeth Sunny

Volume/Issue : Volume 5 - 2020, Issue 4 - April

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://bit.ly/3f079vZ

The project builds a complete computerized health- care system embedded with machine learning applications. A patient’s health data are generally stored in a centralized third party, such as the hospital database or cloud, and make users lose control of their health data, which can easily result in privacy leakage. So here we propose a healthcare system which is focused on the complete computerization of healthcare with the help of a unique Medical Card available to every person. Electronic Medical Records(EMRs) are used for storing medical diagnosis and prescription details of patients. The EMRs of a patient lets doctors know about the complete medical history of their patients. This Health Chain can be integrated with machine learning for applications like disease prediction, doctor recommendation. Disease prediction is all about predicting diseases based on earlier symptoms of a patient while doctor recommendation finds out the best and nearby doctors a person should consult based on his/her disease.The system also has a COVID’19 chatbot which interviews the user and predicts his/her probability of being affected with the disease and suggest necessary actions to take.

Keywords : Decision Tree, Sentimental Analysis, Naive Bayes Algorithm, K-fold Cross Validation.

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Paper Submission Last Date
31 - May - 2022

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