Predictive Analysis of Diabetes Mellitus Using Machine Learning Algorithms

Abstract: Computer vision and pose estimation are essential in analyzing exercise form quality. Tools like MediaPipe can enhance these analyses by providing real-time feedback on body posture. Machine learning techniques, such as random forest algorithms, can be employed to evaluate exercise performance. Cosine similarity can help in comparing different exercise postures to determine alignment and efficiency. Diabetes mellitus is a chronic metabolic disorder where insulin production or effectiveness is compromised. This leads to elevated blood glucose levels, which can result in various health complications. Understanding the role of insulin is crucial for managing diabetes and maintaining overall health. Regular exercise and proper form can significantly contribute to better metabolic control. .

Keywords: Computer Vision · Machine Learning · Predictive Analysis · Diabetes Mellitus · Random Forest