Deep Learning Assisted Diagnosis of Parkinson’s Disease

A neurodegenerative condition that affects the elderly is Parkinson’s disease (PD). A crucial first step in giving quick medical attention is the early diagnosis of PD. The field of artificial intelligence has recently paid increased attention to computer-assisted approaches for PD identification. The suggested method is a strong contender for identifying PD patients. The results of PD symptom monitoring using cost-effective computer tools are useful in telemedicine applications. In this paper, a model is designed to detect PD using an online dataset. Images were resized and analyzed which were classified using the Convolution Neural network (CNN). In novelty, the use of the Nearest Neighbor is used in the Pooling layer. 93% accuracy is attained using the proposed model which results in a 12.9% improvement over other state-of-the-art techniques.