Machine Learning Aiding in the Diagnosis of Parkinson's Disease | Chapter 2 | New Frontiers in Medicine and Medical Research Vol. 9
Parkinson's disease (PD) is a neurological movement illness that is prevalent, progressive, and currently incurable. The diagnosis of Parkinson's disease is difficult, especially in the differential diagnosis of parkinsonism and in the early discovery of the disease. Machine learning techniques have been progressively applied to the diagnosis of PD, with promising findings. Machine learning techniques have been increasingly applied to the diagnosis of PD, with promising results. On magnetic resonance imaging (MRI), resting-state functional MRI (rs-fMRI), diffusion tensor imaging (DTI), and single photon emission computed tomography (SPECT) images, machine learning-based imaging applications have made it possible to automatically differentiate parkinsonism and detect PD at an early stage. In diagnosing PD-associated dopaminergic degeneration, machine learning-based SPECT image analysis apps outperformed conventional semi-quantitative analysis, performed as well as experts, and i...