Latest AI and machine learning research in domestic violence for healthcare professionals.
Purpose: Manual verification of AI-based auto-contouring is labor-intensive and prone to fatigue-related errors. This study developed the large language model (LLM)-based automated Quality Assurance (QA) for auto-contouring (LAQUA) system using a multimodal LLM, Gemini 2.5 Pro, and evaluated its feasibility as a clinical primary screening tool to streamline the QA workflow. Methods: Twenty male pe...
The rapid advancement of AI research automation systems--including AI Scientist, data-to-paper, and Agent Laboratory--has demonstrated the potential for autonomous scientific discovery. However, existing benchmarks for evaluating these systems focus predominantly on fundamental sciences (machine learning, physics, chemistry), overlooking the unique challenges of medical clinical research: complex ...
Background: Previous recommendations on screening for prostate cancer relied on ongoing trials of screening with prostate-specific antigen (PSA), whic...
The identification of suitable lead molecules in the vast chemical space is a critical and challenging task in drug discovery campaigns. Recently, it ...
Background: The FDA Adverse Event Reporting System (FAERS) is a critical pillar of post-marketing pharmacovigilance; however, its utility is constrain...
Robust Support Vector Machines (R-SVMs) address feature noise by adopting a worst-case robust formulation that explicitly incorporates uncertainty set...
Pin sites represent the interface where a metal pin or wire from the external environment passes through the skin into the internal environment of the...
Optical pooled screening (OPS) has emerged as a powerful technique for functional genomics, enabling researchers to link genetic perturbations with co...
Consistency under paraphrase, the property that semantically equivalent prompts yield identical predictions, is increasingly used as a proxy for relia...
Abstract Objective To systematically evaluate the diagnostic performance of large language models (LLMs) in automated medical literature screening and...
Background: Multiple stakeholders need to locate results of registered clinical trials but frequently struggle to find them. Summary results of clinic...
We present KidsNanny, a two-stage multimodal content moderation architecture for child safety. Stage 1 combines a vision transformer (ViT) with an obj...
Falls among older adults can result in hip fractures that requires x-ray based assessment at emergency department (ED). Only 25.7% of patients present...
Background: A critical radiologist shortage exists in India, leading to delayed chest radiograph (CXR) interpretation. This leads to disease progressi...
The rapid evolution of embodied agents has accelerated the deployment of household robots in real-world environments. However, unlike structured indus...
Machine-learned interatomic potentials (MLIPs) are deployed for high-throughput materials screening without formal reliability guarantees. We show tha...
Accurate detection and localization of traumatic injuries in abdominal CT scans remains a critical challenge in emergency radiology, primarily due to ...
Structured radiology reporting promises faster, more consistent communication than free text, but automation remains difficult as models must make man...
The rapid evolution of embodied agents has accelerated the deployment of household robots in real-world environments. However, unlike structured indus...
Machine-learned interatomic potentials (MLIPs) are deployed for high-throughput materials screening without formal reliability guarantees. We show tha...