Prediction of Cardiac Disease using Supervised Machine Learning Algorithms By using Tkinter Frame work

Description

This research work which initiated at an early detection of all the probable symptoms and signs which might further lead to detection of cardiac diseases using data collected from previous patients as well as data input received from the user at that particular time. Instead, a wealth of proposed spatial as well as temporal demographic, and symptom information is available at the data presented during the time of execution. The proposed method incorporates all such information that is being used as a classification approach that compares recent healthcare data against data from that particular baseline distribution using the tkinter application.