Latest AI and machine learning research in risk management for healthcare professionals.
The deployment of large language models (LLMs) for science carries an intrinsic risk: hallucination of citations, fabricated drug approvals or clinical trials, and unsupported experimental outcomes. Here we describe the testing and deployment of a novel systematic, multi-layer approach called the Validation as a System (VaaS) pipeline, iteratively developed during the construction of an open-sourc...
Protein language models (PLMs) are increasingly central to protein engineering and drug discovery. Many high-performing systems, however, rely on large parameter counts, multiple sequence alignments (MSAs), explicit structural inputs, or computationally intensive attention mechanisms, limiting their accessibility and throughput. Here we present AINN-P1, a 167M-parameter protein language model trai...
Agentic vision-language models increasingly act through extended interactions, but most evaluations still focus on single-image, single-turn correctne...
Targeting protein-protein interactions (PPIs) with small molecules is historically challenging due to shallow, solvent-exposed interfaces that lack cl...
Background Narcolepsy is a rare, lifelong neurological disorder that often begins in childhood or adolescence. Diagnosis is frequently delayed because...
Blind Sweep Obstetric Ultrasound (BSOU) enables scalable fetal imaging in low-resource settings by allowing minimally trained operators to acquire sta...
Recent advances in image generation models have expanded their applications beyond aesthetic imagery toward practical visual content creation. However...
Introduction: Timely, protocol-adherent clinical decisions are crucial for reducing neonatal mortality in low-resource settings. Translating extensive...
Electronic Navigational Charts (ENCs) are the safety-critical backbone of modern maritime navigation, yet it remains unclear whether multimodal large ...
Time toxicity, the cumulative healthcare contact days from clinical trial participation, is an important but labor-intensive metric to extract from pr...
Background: Cardiovascular disease (CVD) prevention is limited by the major challenge of low long-term adherence to effective lifestyle regimens. Arte...
Despite the rapid progress of Multimodal Large Language Models (MLLMs), their ability to perform reliable visual grounding in high-stakes clinical sof...
Background: Statistical Analysis Plans (SAPs) are essential for trial transparency and credibility but are resource-intensive to produce. While Large ...
Background: The administrative burden of clinical documentation is a recognised contributor to clinician burnout and diminished care quality. Ambient ...
Reliable product identification from images is a critical requirement in industrial and commercial applications, particularly in maintenance, procurem...
Vision-language process reward models (VL-PRMs) are increasingly used to score intermediate reasoning steps and rerank candidates under test-time scal...
Multi-agent LLM orchestration incurs synchronization costs scaling as O(n x S x |D|) in agents, steps, and artifact size under naive broadcast -- a re...
Increasing staffing constraints and turnaround-time pressures in Prior authorization (PA) have led to increasing automation of decision systems to sup...
Publicly available full-field digital mammography (FFDM) datasets remain limited in size, clinical labels, and vendor diversity, which hinders the tra...
Error detection is crucial in industrial training, healthcare, and assembly quality control. Most existing work assumes a single-view setting and cann...