Language Modeling Screens Parkinson's Disease with Self-reported Questionnaires.

Parkinson's disease (PD) is a growing public health challenge associated with the aging population. Current diagnostic methods rely on motor symptoms and invasive procedures, making early detection difficult. This study established a transferable artificial intelligence (AI) model, Quest2Dx, to analyze health questionnaires to enable low-cost and non-invasive PD diagnosis.

Identifying Progression-Specific Alzheimer's Subtypes Using Multimodal Transformer.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet its current treatments are limited to stopping disease progression. Moreover, the effectiveness of these treatments remains uncertain due to the heterogeneity of the disease. Therefore, it is essential to identify disease subtypes at a very early stage.

Genomics transformer for diagnosing Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease and presents a complex etiology with genomic and environmental factors and no recognized cures. Genotype data, such as single nucleotide polymorphisms (SNPs), could be used as a prodromal factor for early detection of PD. However, the polygenic nature of PD presents a challenge as the complex relationships between SNPs towards disease development are difficult to model.

FairPRS: adjusting for admixed populations in polygenic risk scores using invariant risk minimization.

Polygenic risk scores (PRS) are increasingly used to estimate the personal risk of a trait based on genetics. However, most genomic cohorts are of European populations, with a strong under-representation of non-European groups. Given that PRS poorly transport across racial groups, this has the potential to exacerbate health disparities if used in clinical care.