Latest AI and machine learning research in head trauma for healthcare professionals.
Background: Prognostication after moderate-to-severe traumatic brain injury (TBI) rarely captures lo...
Metabolic dysfunction is increasingly recognized as a risk factor for poor outcomes in breast cancer...
In the treatment of high grade serous ovarian cancer (HGSC), patients initially diagnosed with unres...
Multi-view pose estimation is essential for quantifying animal behavior in scientific research, yet ...
Reinforcement learning (RL) with verifiable rewards (RLVR) has demonstrated the great potential of e...
Pancreatic ductal adenocarcinoma (PDAC) segmentation on contrast-enhanced CT is inherently ambiguous...
The benefits of interventions targeting cognitive aging vary substantially across individuals, large...
The post-training pipeline for diffusion models currently has two stages: supervised fine-tuning (SF...
Background: The Therapeutic Distance framework (Paper 1) achieved AUC 0.61 for orbit-based mortality...
Video depth estimation is essential for providing 3D scene structure in applications ranging from au...
Breath acetone represents a promising non-invasive biomarker for monitoring fat oxidation during exe...
As vision-language models (VLMs) are increasingly deployed in clinical decision support, more than a...
Background: The integration of artificial intelligence (AI) into clinical practice holds transformat...
Background: Women with severe aortic stenosis (AS) are diagnosed later and experience poorer outcome...
Aims: Dynamic left ventricular outflow tract obstruction (LVOTO) is a hemodynamically significant co...
Reliable, minimally invasive biomarkers for predicting immunotherapy response in head and neck squam...
Background: Large language models (LLMs) have been evaluated as tools to assist rare disease diagnos...
The Brain Tumor Reporting and Data System (BT-RADS) standardizes post-treatment MRI response assessm...
LLM post-training pipelines that combine supervised fine-tuning and reinforcement learning are diffi...
The transition from image to video understanding requires vision-language models (VLMs) to shift fro...
Medical visual question answering (Med-VQA) aims to answer clinically relevant questions grounded in...