CureIt – A Multidisease Predictive System using Machine Learning

Abstract

Many contemporary machine learning approaches perform well in predictive analytics on large datasets from many sectors. While predictive analytics in healthcare remains an ambitious goal, it has the potential to enable healthcare practitioners to make more educated decisions regarding patient health and treatment. Globally, mortality from illnesses such as diabetes, heart disease, and breast cancer is frequently caused by a lack of regular checks, even when early indications are present. Limited access to doctors and limited medical infrastructure worsen the problem. The WHO suggests a doctor-to-patient ratio of 1:1000 [8], while India’s ratio of 1:8342 [20] has improved, but distant healthcare access remains a concern. Early diagnosis of heart, cancer, and diabetes-related illnesses has a huge influence on public health. This study aims to use ML algorithms to anticipate illnesses in their early stages. Our team created an online medical test application that uses machine learning to anticipate diseases, with the goal of making healthcare more accessible. Our goal is to develop a web and mobile app that anticipates diseases and provides medical advice, such as diabetes, heart disease, and cancers.

Keywords

• deep learning
• tensorflow
• svm
• logistic regression
• parkinson’s
• diabetes
• tumor
• rf
• ann