An Early-Stage Diabetes Symptoms Detection Prototype using Ensemble Learning
Diabetes; Ensemble Learning; Healthcare; Machine Learning; Smart App
Diabetes is one of the most increasing health issues that the whole world is facing. Recent research has shown that diabetes is spreading quickly in India. Having more than 77 million sufferers, India is actually regarded as the diabetes capital of the world. The lifestyle and eating patterns of people who move from rural to urban settings alter, which raises the prevalence of diabetes. Diabetes has been linked to consequences like vision loss, renal failure, nerve damage, cardiovascular disease, foot ulcers, and digestive issues. Diabetes can harm the blood arteries and neurons in a variety of organs. FPG (Flaccid Plasma Glucose) is a popular test that is done to find out whether a person is a diabetic patient or not. However, not all people consistently take medication and neither monitor their blood sugar levels on a regular basis. Early detection of this disease is also an important thing that people usually don't do. Technology these days has emerged a lot in the healthcare zone. Many prototypes have already been made for the detection of diabetes. The prototype discussed in this paper is an ensemble learning approach for the detection of diabetes in a very early stage. Ensemble learning which includes the use of multiple model prediction has been used to make the outcome stronger and more trustworthy. The overall accuracy achieved by the model is 96.54%. XGBoost also records the minimal execution time of 2.77 seconds only. 2023 IEEE.
Nandi A.; Pal S.; Mishra A.; Sharma V.; Mishra S.; Alkhayyat A.
Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2023, pp. 507-512.
Institute of Electrical and Electronics Engineers Inc.
Nandi A., Kalinga Institute of Industrial Technology, Deemed to Be University, Bhubaneswar, India; Pal S., Kalinga Institute of Industrial Technology, Deemed to Be University, Bhubaneswar, India; Mishra A., Kalinga Institute of Industrial Technology, Deemed to Be University, Bhubaneswar, India; Sharma V., CHRIST (Deemed to Be University), Computer Science Department, Delhi NCR, India; Mishra S., Kalinga Institute of Industrial Technology, Deemed to Be University, Bhubaneswar, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq