Artificial Intelligence Approach for Disease Diagnosis and Treatment
PG Scholar, ME- Department of CSE, PSR Engineering College, Sivakasi, TamilNadu, India.
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Generally, Data mining plays an important role in prediction of diseases in health care industry. The availability of huge amounts of medical data leads to the need for powerful data analysis tools to extract useful knowledge. Medical data are an ever-growing source of information generated from the hospitals in the form of patient records. When mined properly, the information hidden in these records is a huge resource bank for medical research. In this Project, the aim is Medical decision is a highly specialized and challenging job due to various factors, especially in case of diseases that show similar symptoms, or in case of rare diseases. It is a major topic of artificial intelligence in medicine. A Diagnosis Decision Support Systems(DDSS) would take the patients data and propose a set of appropriate Prediction. The system extracts hidden knowledge from a historical heart disease database. This is the most effective model to predict patients with heart disease and use the medical profiles such as age, Blood Pressure and Blood Sugar it can predict the likelihood of patients getting a heart disease. Classification algorithm that has been used with the number of attributes for prediction. Web based questionnaire application can serve a training tool to diagnose the patients with disease. This model could answer complex queries, each with its own strength with respect to ease of model interpretation, access to detailed information and accuracy.