Early - prediction of critical diseases using machine learning and image processing

Abstract

The health care sector experiences a significant transformation. Post-Covid-19, the world undergoes dynamic changes. Many hospitals now offer online consultations. Early intervention is crucial for treating numerous major and minor diseases. The early prediction of a disease, based on image reports, diagnosis reports, or symptoms, allows for prompt treatment by doctors and patients. This system will diagnose various diseases based on given symptoms, including major diseases like multiple types of cancer. The proposed system can identify diseases based on diagnosis report parameters. Machine learning is widely used in the healthcare system for predictions. Three algorithms of machine learning used are to predict the critical diseases - Naive Bayes Decision Tree and Random Forest for more accurate results. Using machine learning algorithms and image processing techniques multiple diseases can be predicted with best accuracy in less time saving in a more safe way