Published Paper Details:

Heart disease is the most prevalent degenerative disease in seniors in which progression can be prevented or delayed by early diagnosis. Heart disease is a term casing any disorder of the heart. Some heart disease leads to death. In order to reduce the number of deaths from heart disease, there has to be a quick and efficient detection technique. This work presents a Machine learning model, involving the mining of texts integrated into the mining of structured data. This model aims to assist specialists in the diagnosis of patients with suspicion of Heart disease. Firstly, we need to collect a set of medical records of different patients who are all having heart disease. Then, a new structured attribute was created from a text mining process. It was the result of predicting the patient�s pathological history information stored in an unstructured textual attribute. J48 algorithm creates a decision tree for machine learning that was applied to obtain the risk level. We may also implement RFID for patients. RFID is known for its distinctive ID number. Using this advantage, in the first part, the monitoring of a patient is done whenever he arrives at the hospital. In case of any shifts from the hospital, the information is still accessible. Every patient is provided with a unique RFID number and all the details relating to the patient and treatments are store in a federal database that is retrieved by the server.