Abstract
Machine learning-based smart health prediction is a fast- expanding topic that has the potential to completely change how we identify and treat diseases. We can create systems that can accurately forecast a patient's risk of contracting a disease or their chance of responding to a particular treatment by utilizing machine learning algorithms to examine enormous quantities of medical data.Although they are still in the early stages of research, smart health prediction systems could have a significant influence on how medicine is practiced in the future. Systems for making smart predictions about a person's health have the potential to boost healthcare delivery's effectiveness and quality. We can put preventative measures in place to lower a patient's risk of contracting a disease by precisely anticipating the patient's risk. Smart health prediction systems can also be used to pinpoint people who are most at risk for developing complications from an illness or who are most likely to have poor treatment outcomes. These data can be used to develop personalized treatment plans for patients.
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