Background: Per- and polyfluoroalkyl substances (PFAS), particularly perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent organic pollutants ubiquitous in the environment. Epidemiological evidence has closely linked them... read more
Biologically informed neural networks (BINNs), also known as visible neural networks (VNNs), are widely adopted in omics because their architectures mirror known biological structures, such as gene-to-pathway relationships, and are therefore often as... read more
Translating transcriptomic data into therapeutic hypotheses remains fragmented and labor-intensive. Here we present ConvergeCELL, a platform combining a patient representation model trained on over 20 million cells across 4,479 patients, an interpret... read more
Syntaxin-binding protein 1 (STXBP1) mutations lead to severe epilepsy, intellectual disability, developmental delay, and movement disorder. Effective treatments for these conditions do not exist. Recent studies in Munc18-1 (STXBP1) C.elegans models d... read more
Whole-body SPECT bone scintigraphy reflects skeletal metabolic activity throughout the body and plays an indispensable role in the screening, treatment evaluation, and prognostic assessment of bone metastases in tumors. However, the automatic detecti... read more
We introduce ClaroAI-Bench, an evaluation suite for measuring AI agents' ability to reproduce computational findings from published biomedical research. The benchmark comprises 35 real NIH-funded papers spanning five modalities (genomics, imaging, cl... read more
Predicting cellular responses to genetic or chemical perturbations across biological contexts is central to drug development and disease understanding.Despite increases in data and model scale, deep learning models have not consistently outperformed ... read more
Stroke starts as a focal vascular lesion, but its structural consequences often extend beyond the lesion site, resulting in distributed brain atrophy whose organizing principles remain unclear. Here, using longitudinal MRI data from two stroke cohort... read more
Generative models are increasingly used for protein design, but the lack of standardized evaluation frameworks limits comparison across model classes and hinders translation to experimental success. Here, we introduce a unified sampling and benchmark... read more
Identifying causal relationships, rather than mere associations, is essential for applications such as finding genes driving diseases and guiding drug discovery towards disease mechanisms rather than symptom management. Although many studies extract ... read more
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.