Diabetes and heart disease identification using biomedical iris data
Sanjeev Kumar Punia, Manoj Kumar, Surendra Kumar Pathak, Xiaochun Cheng · Applied and Computational Engineering · 2023
The World Health Organization (WHO) report shows that Heart disease is the major cause of death all over the world i.e. nearly 21.2 million people die every year directly or indirectly from Cardiovascular (Heart) diseases estimated 32% of all deaths worldwide. Whereas, Diabetes is at the ninth position for the death all over the world i.e. nearly 3.7 million people die every year from diabetes estimated 6.61% of all deaths worldwide. The Heart and Pancreas organ play a most important role in human being. The blood flows in all parts of the body through heart. The function of pancreas is to regulate maintain the insulin levels that is responsible for diabetes. The detection of heart disease and diabetes takes too much time and very costly process. In our research, we develop a Heart Disease and Diabetes Identification System based on Iris Healthcare Kiosk. We proposed a desktop system application that detects these diseases through the Iris. The process starts by taking the left Eye photograph of the patient's through Eyeronec (company name) camera and perform intermediates operations of target cropping, pre-processing, auto-cropping (through integral projection and removing sclera), heart regions of interest (ROI) measuring, pancreatic measuring, extracting the feature and finally classify in the result. The classification result shows that 83% tests are successful, 11% tests are scant whereas 6% tests became fail. The operation is performed on 32 different training digital data sets and final result is labelled as normal or abnormal. The result shows that accuracy of our proposed system in heart disease and diabetes are 86.36% and 90.91% respectively.