An Autonomous Sensory Approach: Artrial Fibrillation through Parkinson’s disease Hybrid Approach to Optimized Increased Risk

Artrial fibrillation (AF) is a support and beginning of non-train side effects of Parkinson’s disease which act as an autonomic sensory system. Worldly relationship among PD and AF. The tedious and perplexing for AF is a neurological issue, hence PD has exacted and proficient finding of clinical experts and physicians as professionals. Parkinson’s and AF are used to identify and computed the resultant for ML. This paper study Gradient boosting with L1_regularization and GB model is used. The proposed framework using KNN the cross-validation strategy is implemented. The performance metrics such as accuracy, precision, Kappa, sensitivity, f1score with their execution time etc. it computed the model performance on the basis of disease symptoms as for Parkinson and AF disease that are related to each other. The prosed framework and the model are used to evaluated the feature dataset selection and the various classification methods.to detect and diagnose the voice patterns by their recordings of patients. The results are computed by Gradient boosting -L1 for PD and AF are 99.9% in terms of accuracy rate.