HEALTHCURE- MACHINE LEARNING APPLICATION FOR MULTIPLE DISEASE PREDICTION

Computer Engineering

industries, including healthcare. Because machine learning algorithms can forecast multiple diseases at once, they can potentially improve patient outcomes and alter medical diagnoses. Many machine learning techniques can perform predictive analytics on large amounts of data from many industries. Predictive analytics can be difficult to use in the healthcare industry, but over time, with extensive data analysis, it can assist doctors in making timely decisions regarding the health and treatment plans of their patients. A single ailment at a time is the subject of many machine learning algorithms currently used for health care analysis. For example, the first is used to analyze diabetes, the second to analyze heart disease, and so on. A person must visit several websites to anticipate more than one sickness. A single analysis cannot forecast more than one disease under any common framework. The accuracy of some of the models is worse than others, which can have a major impact on patient care. The test web application uses machine learning to anticipate different diseases, making the process smooth and accessible to the public. Our goal in this study is to create a web application that predicts diseases by utilizing machine learning to make predictions about various illnesses, including heart disease, diabetes, and lung cancer. It could help healthcare professionals make better judgments, improve patient care, and better allocate resources within healthcare systems. It also has the potential for population-level disease surveillance, which would help public health officials quickly identify illness outbreaks and put preventive measures in place.

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