Practice Management

Nomenclature Ontology for Medical And Disease names (NOMAD): taxonomy of types and origins of disease names

The nomenclature of human disease has developed organically over the past centuries using Greek, Latin, and Arabic terminology and reflects the idiosyncrasies of different eras of medical discovery. Despite evident heterogeneity in naming practices, no systematic framework exists for characterising these conventions across all diseases. In this paper, we describe the Nomenclature Ontology for Medi...

JSCGC: Joint Source-Channel-Generation Coding for Wireless Generative Communications

Conventional communication systems, including both separation-based coding and learning-based joint source-channel coding (JSCC), are typically designed under Shannon's rate-distortion theory. However, relying on generic distortion metrics fails to capture complex human visual perception, often resulting in blurred or unrealistic reconstructions. In this paper, we propose Joint Source-Channel-Gene...

Topological Deep Learning Identifies Polygenic Variant Clusters Across Familial Multimorbid Disorders

Whole-genome sequencing comprehensively captures coding, non-coding and structural variation in families with suspected inherited disorders, yet its c...

Comprehensive evaluation of LLM capabilities for interpretation and analysis of genome-scale metabolic models in metabolic engineering

Genome-scale metabolic models (GSMs) underpin pathway and strain engineering by linking genes to metabolic reactions and enabling system-level simulat...

CREP: Cis-Regulatory Element Predictor Based on Fine-Tuned Enformer

A substantial fraction of disease-associated genetic variants reside in non-coding regions of the genome, where they act by perturbing cis-regulatory ...

Beyond Output Matching: Preserving Internal Geometry in NVFP4 LLM Distillation

Demand for low-precision inference, including NVFP4-based approaches, has grown as large language models are increasingly deployed in latency and cost...

Measuring the sensitivity of LLM-based structured extraction to prompt, model, and schema choices in clinical discharge summaries

Large language models are increasingly used for structured extraction from clinical free-text notes, but the sensitivity of their output to upstream c...

To RAG, or Not to RAG? A Comparative Evaluation of Retrieval-Augmented Generation for ICD Coding of German Tumor Diagnoses

Introduction Coding tumor diagnoses from free-text clinical documentation currently requires substantial manual effort. Promising approaches for autom...

gTranslate: rapid and accurate translation table prediction for prokaryotic genomes

Background: Bioinformatic tools often require the prediction of protein-coding genes to make inferences about prokaryotic genomes. Typically, the gene...

An ECG foundation model for generalizable cardiac function prediction across the lifespan

Background Artificial intelligence-enhanced electrocardiography (AI-ECG) enables scalable, low-cost cardiac dysfunction screening, but existing models...

Professionalism Pulse: Development and Validation of a Natural Language Processing Pipeline and Dashboard for Safety Culture Surveillance in NYC Health + Hospitals

Background: Professionalism and effective communication are foundational determinants of patient safety and quality of care. Unprofessional behaviors ...

Prediction of Transcription Factor DNA Binding Affinity with High-Throughput Kd Measurements and Deep Learning

Transcription factors (TFs) regulate gene expression through specific interactions with genomic DNA. While TF binding motifs from public databases des...

Predictive coding video models capture dorsal parietal representations and human judgments for surfaces defined by motion

Stimulus-computable models have transformed our understanding of ventral visual processing, yet comparable progress in modeling the dorsal visual stre...

Mapping the combinatorial coding between olfactory receptors and perception with deep learning

The sense of smell remains poorly understood, especially in contrast to visual and auditory coding. At the core of our sense of smell is the olfactory...

Rethinking Low-Light Image Enhancement: A Log-Domain Intensity--Chromaticity Decoupling Perspective

Explicit reconstruction constraints derived from the decoupled representation are further imposed to suppress abnormal channel amplification and chrom...

Polysemanticity in human hippocampal neurons

To comprehend language, the brain must navigate a high-dimensional semantic landscape while seamlessly contextualizing meaning. Inspired by recent adv...

NeuroCDS: Integrating Local and Global Neural Network Representations via Structural Constrained Viterbi Decoding for Robust CDS Annotation

Motivation: Robust annotation of Coding Sequences (CDS) is critical for downstream transcriptomics, yet heavily fragmented de novo RNA-Seq assemblies ...

Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization

Learning meaningful representations from medical time series (MedTS) such as ECG or EEG signals is a critical challenge. These signals are often high-...

Sniffing Shapes Dopamine Signals for Reward Prediction

Adaptive behaviors depend on predicting outcomes from sensory evidence. Dopamine neurons in the ventral tegmental area (VTA) broadcast reward-predicti...

Fast learning, memorization and generalization: A computational characterization of sparse to dense hippocampal-cortical codes

Classic findings from neuropsychology and animal studies established the hippocampus as a key substrate for rapid learning and episodic memory, with t...