AUTOMATIC MULTI-DISEASES PREDICTION USING MACHINE LEARNING

A. Akhila, K. Hemalatha, A. Navya, B. Tejaswi, K. Hemanth, Ramesh Alladi
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Abstract

Disease prediction has become one of the most difficult challenges in medicine in recent years. To eliminate the hazards connected with prediction, it is necessary to automate the process and notify the patient well in advance. The medical database is mostly made up of discrete data. As a result, making decisions using discrete data is a difficult task. Machine learning simplifies the process. The major purpose of this research is to give doctors a tool to diagnose diseases in their early stages. This model includes a user interface that allows users to anticipate ailments such as heart disease, Parkinson's disease, cancer, and diabetes. We utilized SVM and Logistic Regression for classification.
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基于机器学习的多疾病自动预测
近年来,疾病预测已成为医学领域最困难的挑战之一。为了消除与预测相关的危险,有必要使该过程自动化并提前通知患者。医学数据库大多由离散数据组成。因此,使用离散数据做出决策是一项艰巨的任务。机器学习简化了这个过程。这项研究的主要目的是为医生提供一种早期诊断疾病的工具。该模型包括一个用户界面,允许用户预测心脏病、帕金森病、癌症和糖尿病等疾病。我们使用支持向量机和逻辑回归进行分类。
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