Neurology

Head Trauma

Latest AI and machine learning research in head trauma for healthcare professionals.

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Post-Incorporating Code Structural Knowledge into LLMs via In-Context Learning for Code Translation

Code translation migrates codebases across programming languages. Recently, large language models ...

Improving Quantization with Post-Training Model Expansion

The size of a model has been a strong predictor of its quality, as well as its cost. As such, the ...

Post-composing ontology terms for efficient phenotyping in plant breeding.

Ontologies are widely used in databases to standardize data, improving data quality, integration, an...

Mar 2025 40117331
Free-Lunch Color-Texture Disentanglement for Stylized Image Generation

Recent advances in Text-to-Image (T2I) diffusion models have transformed image generation, enablin...

ACT360: An Efficient 360-Degree Action Detection and Summarization Framework for Mission-Critical Training and Debriefing

Effective training and debriefing are critical in high-stakes, mission-critical environments such ...

When neural implant meets multimodal LLM: A dual-loop system for neuromodulation and naturalistic neuralbehavioral research

We propose a novel dual-loop system that synergistically combines responsive neurostimulation (RNS...

LHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds

Animatable 3D human reconstruction from a single image is a challenging problem due to the ambigui...

Markerless Tracking-Based Registration for Medical Image Motion Correction

Our study focuses on isolating swallowing dynamics from interfering patient motion in videofluoros...

Deformable Registration Framework for Augmented Reality-based Surgical Guidance in Head and Neck Tumor Resection

Head and neck squamous cell carcinoma (HNSCC) has one of the highest rates of recurrence cases amo...

Periodontal Bone Loss Analysis via Keypoint Detection With Heuristic Post-Processing

Calculating percentage bone loss is a critical test for periodontal disease staging but is sometim...

Hyperspectral Image Restoration and Super-resolution with Physics-Aware Deep Learning for Biomedical Applications

Hyperspectral imaging is a powerful bioimaging tool which can uncover novel insights, thanks to it...

Causal Tree Extraction from Medical Case Reports: A Novel Task for Experts-like Text Comprehension

Extracting causal relationships from a medical case report is essential for comprehending the case...

PEO: Improving Bi-Factorial Preference Alignment with Post-Training Policy Extrapolation

The alignment of large language models with human values presents a critical challenge, particular...

EXACT-CT: EXplainable Analysis for Crohn's and Tuberculosis using CT

Crohn's disease and intestinal tuberculosis share many overlapping features such as clinical, radi...

AutoComb: Automated Comb Sign Detector for 3D CTE Scans

Comb Sign is an important imaging biomarker to detect multiple gastrointestinal diseases. It shows...

BarkXAI: A Lightweight Post-Hoc Explainable Method for Tree Species Classification with Quantifiable Concepts

The precise identification of tree species is fundamental to forestry, conservation, and environme...

Responsible AI Agents

Thanks to advances in large language models, a new type of software agent, the artificial intellig...

LAM: Large Avatar Model for One-shot Animatable Gaussian Head

We present LAM, an innovative Large Avatar Model for animatable Gaussian head reconstruction from ...

Clinical Inspired MRI Lesion Segmentation

Magnetic resonance imaging (MRI) is a potent diagnostic tool for detecting pathological tissues in...

MHQA: A Diverse, Knowledge Intensive Mental Health Question Answering Challenge for Language Models

Mental health remains a challenging problem all over the world, with issues like depression, anxie...

PQBFL: A Post-Quantum Blockchain-based Protocol for Federated Learning

One of the goals of Federated Learning (FL) is to collaboratively train a global model using local...

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