A stacked multi-classifier for multi-modal data fusion in transcranial sonography-based Parkinson’s disease assessment

Abstract Parkinson’s disease (PD) is a catastrophic neurodegenerative disorder and a major culprit of neurological disability worldwide. Accurate diagnosis of PD, especially in its early stages, is paramount for timely intervention and effective therapeutic management. However, contemporary clinical diagnostic methods are hindered by the complexities of procedures, inter-evaluator subjectivity, and challenges related to the accuracy and reproducibility of diagnoses.