Pain Management

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Beyond Accuracy: Evaluating Visual Grounding In Multimodal Medical Reasoning

Recent work shows that text-only reinforcement learning with verifiable rewards (RLVR) can match or ...

Autoencoders for unsupervised analysis of rat myeloarchitecture

Quantitative assessment of brain histology is often constrained by predefined feature sets and labor...

NeighborMAE: Exploiting Spatial Dependencies between Neighboring Earth Observation Images in Masked Autoencoders Pretraining

Masked Image Modeling has been one of the most popular self-supervised learning paradigms to learn r...

NICO-RAG: Multimodal Hypergraph Retrieval-Augmented Generation for Understanding the Nicotine Public Health Crisis

The nicotine addiction public health crisis continues to be pervasive. In this century alone, the to...

When Does Multimodal Learning Help in Healthcare? A Benchmark on EHR and Chest X-Ray Fusion

Machine learning holds promise for advancing clinical decision support, yet it remains unclear when ...

NESTOR: A Nested MOE-based Neural Operator for Large-Scale PDE Pre-Training

Neural operators have emerged as an efficient paradigm for solving PDEs, overcoming the limitations ...

RelA-Diffusion: Relativistic Adversarial Diffusion for Multi-Tracer PET Synthesis from Multi-Sequence MRI

Multi-tracer positron emission tomography (PET) provides critical insights into diverse neuropatholo...

Causal Decoding for Hallucination-Resistant Multimodal Large Language Models

Multimodal Large Language Models (MLLMs) deliver detailed responses on vision-language tasks, yet re...

Evaluating the AI Potential as a Safety Net for Diagnosis: A Novel Benchmark of Large Language Models in Correcting Diagnostic Errors

Background: Diagnostic errors are a leading cause of preventable patient harm, often occurring durin...

Sequential Counterfactual Inference for Temporal Clinical Data: Addressing the Time Traveler Dilemma

Counterfactual inference enables clinicians to ask "what if" questions about patient outcomes, but s...

Mobile-O: Unified Multimodal Understanding and Generation on Mobile Device

Unified multimodal models can both understand and generate visual content within a single architectu...

PaReGTA: An LLM-based EHR Data Encoding Approach to Capture Temporal Information

Temporal information in structured electronic health records (EHRs) is often lost in sparse one-hot ...

Mobile-O: Unified Multimodal Understanding and Generation on Mobile Device

Unified multimodal models can both understand and generate visual content within a single architectu...

Balanced deep learning on multi-omics networks identifies molecular subgroups of pathological brain aging

Abstract Background Neurodegenerative diseases, including Alzheimer's disease (AD), exhibit substant...

QuPAINT: Physics-Aware Instruction Tuning Approach to Quantum Material Discovery

Characterizing two-dimensional quantum materials from optical microscopy images is challenging due t...

Explainable AI: Context-Aware Layer-Wise Integrated Gradients for Explaining Transformer Models

Transformer models achieve state-of-the-art performance across domains and tasks, yet their deeply l...

Natural Language Processing Analysis of Australian Health Practitioner Disciplinary Tribunal Decisions, 1999-2026

Background: Australian health practitioners are regulated under the Health Practitioner Regulation N...

Comparing AI and Human Coding of NIH Grant Abstracts to Identify Innovations in Opioid Addiction Treatment

Large language models (LLMs) are increasingly used for qualitative analysis in substance use researc...

Multimodal gene embeddings for drug-target prediction and lineage reconstruction

Understanding how gene function emerges across molecular, cellular, and pharmacologic contexts remai...

Uncertainty-Aware Vision-Language Segmentation for Medical Imaging

We introduce a novel uncertainty-aware multimodal segmentation framework that leverages both radiolo...

OPBench: A Graph Benchmark to Combat the Opioid Crisis

The opioid epidemic continues to ravage communities worldwide, straining healthcare systems, disrupt...

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