output
20142026
most citedLLMCARE: early detection of cognitive impairment via transformer models enhanced by LLM-generated synthetic data

6 citations

35 papers

q-bio.NC2026

Cross-scale spatially-aware generative modeling of transcriptomic programs underlying neurodegenerative brain organization

Krishnakumar Vaithianathan

Neurodegenerative disorders such as Alzheimer's disease exhibit highly organized patterns of regional brain vulnerability, yet the biological mechanisms underlying this spatial sel…

cs.CV2026

Understanding Sources of Demographic Predictability in Brain MRI via Disentangling Anatomy and Contrast

Mehmet Yigit Avci, Akshit Achara, Andrew King +1

Demographic attributes can be predicted from medical images, raising concerns about bias in clinical AI systems. In X-ray imaging, acquisition characteristics have been shown to co…

stat.ME2026

Improving operating characteristics of clinical trials by augmenting control arm using propensity score-weighted borrowing-by-parts power prior

Apu Chandra Das, Sakib Salam, Aninda Roy +3

Borrowing external data can improve estimation efficiency but may introduce bias when populations differ in covariate distributions or outcome variability. A proper balance needs t…

q-bio.GN2026

MethConvTransformer: A Deep Learning Framework for Cross-Tissue Alzheimer's Disease Detection

Gang Qu, Guanghao Li, Zhongming Zhao

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by progressive cognitive decline and widespread epigenetic dysregulation in the brain. DNA met…

cs.LG2025★ 1 cited

R-GenIMA: Integrating Neuroimaging and Genetics with Interpretable Multimodal AI for Alzheimer's Disease Progression

Kun Zhao, Siyuan Dai, Yingying Zhang +9

Early detection of Alzheimer's disease (AD) requires models capable of integrating macro-scale neuroanatomical alterations with micro-scale genetic susceptibility, yet existing mul…

stat.CO2025

Alzheimer's Clinical Research Data via R Packages: the alzverse

Michael C. Donohue, Kedir Hussen, Oliver Langford +3

Sharing clinical research data is essential for advancing research in Alzheimer's disease (AD) and other therapeutic areas. However, challenges in data accessibility, standardizati…