Brain Disease Parkinson's Diagnosis using VGG-16 and VGG-19 with Spiral and Waves drawings as Input

After Alzheimer's disease, Parkinson's disease (PD) is a prominent disease that falls within the category of neurodegenerative disorders and dementia. There is no known etiology for this illness. PD has an impact on motor control. It usually starts slowly and can have minimal symptoms at first. It also usually advances slowly over time. For those with Parkinson's disease (PD), there are medications available to control symptoms and enhance quality of life. To preserve the patient's life, an early diagnosis of the illness is essential. Early diagnosis of such complicated disorders is one of the most elusive goals in healthcare. The current task involves using neuropsychological testing, such as obtaining patient drawings, to identify the illness. These illustrations could be of waves, spirals, clocks, etc. In this case, the model based on VGG-16 and VGG-19 is regarded to have input in the form of spiral and waves. The model's output, which has an accuracy of above 0.83, illustrates the overfitting that commonly happens, especially in complex models. It's crucial to strike a balance. It is essential to regularly observe and modify the model using performance metrics on untested data in order to ensure the model's good generalization to novel settings.