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Neurology Subcategories: Autism Dementia Head Trauma Parkinson's Disease Seizures Sleep Disorders

Showing 862-882 of 6,678 articles

An inherently interpretable AI model improves screening speed and accuracy for early diabetic retinopathy.

Diabetic retinopathy (DR) is a frequent complication of diabetes, affecting millions worldwide. Scre...

May 2025 40354306

TRUST: An LLM-Based Dialogue System for Trauma Understanding and Structured Assessments

Objectives: While Large Language Models (LLMs) have been widely used to assist clinicians and supp...

Apr 2025 http://arxiv.org/abs/2504.21851v1

How Real Are Synthetic Therapy Conversations? Evaluating Fidelity in Prolonged Exposure Dialogues

The growing adoption of synthetic data in healthcare is driven by privacy concerns, limited access...

Apr 2025 http://arxiv.org/abs/2504.21800v3

In defence of post-hoc explanations in medical AI

Since the early days of the Explainable AI movement, post-hoc explanations have been praised for t...

Apr 2025 http://arxiv.org/abs/2504.20741v1

WILD: a new in-the-Wild Image Linkage Dataset for synthetic image attribution

Synthetic image source attribution is an open challenge, with an increasing number of image genera...

Apr 2025 http://arxiv.org/abs/2504.19595v2

Proof-of-TBI -- Fine-Tuned Vision Language Model Consortium and OpenAI-o3 Reasoning LLM-Based Medical Diagnosis Support System for Mild Traumatic Brain Injury (TBI) Prediction

Mild Traumatic Brain Injury (TBI) detection presents significant challenges due to the subtle and ...

Apr 2025 http://arxiv.org/abs/2504.18671v1

Lightweight Social Computing Tools for Undergraduate Research Community Building

Many barriers exist when new members join a research community, including impostor syndrome. These...

Apr 2025 http://arxiv.org/abs/2504.16366v1

Optimizing Post-Cancer Treatment Prognosis: A Study of Machine Learning and Ensemble Techniques

The aim is to create a method for accurately estimating the duration of post-cancer treatment, par...

Apr 2025 http://arxiv.org/abs/2504.16135v1

Post-Hurricane Debris Segmentation Using Fine-Tuned Foundational Vision Models

Timely and accurate detection of hurricane debris is critical for effective disaster response and ...

Apr 2025 http://arxiv.org/abs/2504.12542v2

Thousand Voices of Trauma: A Large-Scale Synthetic Dataset for Modeling Prolonged Exposure Therapy Conversations

The advancement of AI systems for mental health support is hindered by limited access to therapeut...

Apr 2025 http://arxiv.org/abs/2504.13955v4

Uncertainty-Guided Coarse-to-Fine Tumor Segmentation with Anatomy-Aware Post-Processing

Reliable tumor segmentation in thoracic computed tomography (CT) remains challenging due to bounda...

Apr 2025 http://arxiv.org/abs/2504.12215v1

A Category-Fragment Segmentation Framework for Pelvic Fracture Segmentation in X-ray Images

Pelvic fractures, often caused by high-impact trauma, frequently require surgical intervention. Im...

Apr 2025 http://arxiv.org/abs/2504.11872v1

DamageCAT: A Deep Learning Transformer Framework for Typology-Based Post-Disaster Building Damage Categorization

Natural disasters increasingly threaten communities worldwide, creating an urgent need for rapid, ...

Apr 2025 http://arxiv.org/abs/2504.11637v1

Hyperlocal disaster damage assessment using bi-temporal street-view imagery and pre-trained vision models

Street-view images offer unique advantages for disaster damage estimation as they capture impacts ...

Apr 2025 http://arxiv.org/abs/2504.09066v1

Are We Merely Justifying Results ex Post Facto? Quantifying Explanatory Inversion in Post-Hoc Model Explanations

Post-hoc explanation methods provide interpretation by attributing predictions to input features. ...

Apr 2025 http://arxiv.org/abs/2504.08919v1

The Lyme Disease Controversy: An AI-Driven Discourse Analysis of a Quarter Century of Academic Debate and Divides

The scientific discourse surrounding Chronic Lyme Disease (CLD) and Post-Treatment Lyme Disease Sy...

Apr 2025 http://arxiv.org/abs/2504.08777v1

SHapley Estimated Explanation (SHEP): A Fast Post-Hoc Attribution Method for Interpreting Intelligent Fault Diagnosis

Despite significant progress in intelligent fault diagnosis (IFD), the lack of interpretability re...

Apr 2025 http://arxiv.org/abs/2504.03773v1

Detecting PTSD in Clinical Interviews: A Comparative Analysis of NLP Methods and Large Language Models

Post-Traumatic Stress Disorder (PTSD) remains underdiagnosed in clinical settings, presenting oppo...

Apr 2025 http://arxiv.org/abs/2504.01216v1

Multimodal LLMs for OCR, OCR Post-Correction, and Named Entity Recognition in Historical Documents

We explore how multimodal Large Language Models (mLLMs) can help researchers transcribe historical...

Apr 2025 http://arxiv.org/abs/2504.00414v1

Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network

Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient manag...

Mar 2025 http://arxiv.org/abs/2504.01025v1

DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers

Text-to-image generation models, especially Multimodal Diffusion Transformers (MMDiT), have shown ...

Mar 2025 http://arxiv.org/abs/2503.22796v1