AI can detect Parkinson's from nighttime breathing patterns

In a recent Nature Medicine journal study, researchers develop an artificial intelligence (AI)-based model to detect Parkinson's disease (PD) and track its progression from nocturnal breathing signals. Since PD is the fastest-growing neurological disease worldwide, there is an urgent need for novel diagnostic biomarkers that can detect the disease at an early stage. Currently, there are no drugs capable of reversing or ceasing PD progression. Furthermore, PD is typically diagnosed based on changes in motor functions, such as tremors and rigidity. The assessment of PD progression primarily relies on patient self-reporting; however, clinicians also use the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) for qualitative PD assessment. Some existing PD biomarkers, including cerebrospinal fluid, blood biochemical, and neuroimaging, have shown promising results for their potential utility in the early diagnosis of this disease.