Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,461 to 1,470 of 234,892 articles

DNA-LLM2Vec: Architecture-Aware Task-Conditioned Adaptation of Decoder DNA Foundation Models

bioRxiv
Decoder DNA foundation models pretrain with dense next-token prediction and scale to long sequences, but their representations are directional. This is a poor fit for genomic tasks that need sequence context both upstream and downstream of a locus. B... read more 

FERDINAND: An Open Framework for Download and AI-ready Preprocessing of IMPC 2D Radiographs

bioRxiv
The International Mouse Phenotyping Consortium (IMPC) maintains a large archive of whole-body dorsoventral radiographs. However, heterogeneity in file formats, metadata completeness, orientation, and image quality limits its reuse for large-scale qua... read more 

NIK stabilization reprograms the pancreas toward chronic pancreatitis and pancreatic lipomatosis

bioRxiv
Pancreatic lipomatosis, characterized by progressive adipose replacement of the exocrine pancreas, is a known consequence of chronic pancreatitis. Despite its clinical relevance, the mechanisms driving lipomatosis remain poorly understood. Here, we u... read more 

From Closed-Set Annotation to In-Context Discovery: Biologically Grounded LLMs for Cellular Profiling

bioRxiv
Tumour heterogeneity reflects both cellular identity (lineage) and state (active transcriptional programs), yet computational methods generally analyse these axes separately. We introduce CellScribe, a generative framework that conditions a pretraine... read more 

SVC: A Vision Transformer-based Spatially and Virtually Embedded Cell Model for Deciphering Subcellular Spatial Transcriptomic Heterogeneity

bioRxiv
Subcellular transcript localization shapes gene regulation and cellular function, yet profiling it at scale remains difficult, limiting our ability to study subcellular heterogeneity across tissues and disease. Here, we present SVC, a Vision Transfor... read more 

Decoding super-enhancer regulatory grammar and pathogenic gain-of-function variants directly from DNA sequence

bioRxiv
Super-enhancers (SEs) drive cell-identity gene expression, yet their identification relies on epigenomic profiling (e.g., H3K27ac ChIP-seq), precluding discovery in unprofiled cellular states and leaving their underlying sequence grammar unknown. Her... read more 

LuTuFlow: a deep learning-based pipeline for quantitative characterization of mouse lung tumors in CT imaging

bioRxiv
Computed tomography (CT) is a widely used, non-invasive imaging tool to monitor tumor growth. Tumor identification and volumetric quantification are crucial for assessing tumor burden, whereas tracking individual tumors by aligning scans from multipl... read more 

AI-ASSISTED NANOMEDICINE REVEALS SYSTEMIC IMMUNE IMPACT IN OVARIAN CANCER METASTASIS

bioRxiv
Ovarian cancer, a gynecological malignancy, poses a significant challenge as researchers struggle to comprehend how tumor cells communicate with the immune system. Ovarian tumors contain both bulk cancer cells and cancer stem cells (CSCs), which are ... read more 

Deep learning-based prediction of wall shear stress throughout the cardiac cycle in middle cerebral artery bifurcation aneurysms

bioRxiv
Background and Objective: Cardiac-cycle wall shear stress (WSS) is relevant to intracranial aneurysm hemodynamic assessment, but transient computational fluid dynamics (CFD) is costly. Existing surrogates use steady-flow priors or joint steady/transi... read more 

Chemical foundation models reveal molecular principles underlying glycobiology

bioRxiv
Glycans encode biological specificity through branching, linkage and stereochemical diversity, and have traditionally been modelled using specialised computational representations distinct from those developed for general chemistry. It remains unclea... read more