Latest AI and machine learning research in emergency medicine for healthcare professionals.
Current video benchmarks for multimodal large language models (MLLMs) focus on event recognition, temporal ordering, and long-context recall, but overlook a harder capability required for expert procedural judgment: tracking how ongoing interactions update the procedural state and thereby determine the correctness of later actions. We introduce SiMing-Bench, the first benchmark for evaluating this...
Current operational Earth Observation (EO) services, including the Copernicus Emergency Management Service (CEMS), the European Forest Fire Information System (EFFIS), and the Copernicus Land Monitoring Service (CLMS), rely primarily on ground-based processing pipelines. While these systems provide mature large-scale information products, they remain constrained by downlink latency, bandwidth limi...
Patient healthcare utilization consists of irregularly time-stamped events, such as outpatient visits, inpatient admissions, and emergency encounters,...
Biological neural networks are characterized by short average path lengths, high clustering, and modular and hierarchical architectures. These complex...
Healthcare system performance evaluation is constrained by episodic performance indicators and process mining techniques that fail to accommodate the ...
Innate immune cells contribute to both secondary brain injury and repair following intracerebral hemorrhage (ICH). However, the specific signaling pat...
Type A Aortic Dissection (TAAD) is a life-threatening cardiovascular emergency that demands rapid and precise preoperative evaluation. While key anato...
Purpose: Early recognition of deterioration in patients with suspected infection at the emergency department (ED) is important. Current clinical scori...
Background Chronic subdural hematoma (cSDH) recurrence requiring reoperation occurs in 5-33% of cases, representing a substantial clinical and economi...
Smart glass is emerging as an useful device since it provides plenty of insights under hands-busy, eyes-on-task situations. To understand the context ...
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...
Introduction: Timely, protocol-adherent clinical decisions are crucial for reducing neonatal mortality in low-resource settings. Translating extensive...
Current clinical evaluations of large language models (LLMs) rely on datasets which fail to reflect real-world medical complexity. We developed a high...
End-to-end text-image machine translation (TIMT), which directly translates textual content in images across languages, is crucial for real-world mult...
Federated Learning (FL), as a popular distributed learning paradigm, has shown outstanding performance in improving computational efficiency and prote...
Vision Language Models (VLMs) are increasingly used for tasks like medical report generation and visual question answering. However, fluent diagnostic...
Systems powered by large language models are widely used for health information and advice, yet robust evidence for their safety and effectiveness in ...
Frontier language models are widely used for health-related queries, yet aggregate benchmark scores do not capture safety implications of errors. We a...
Background Scalable, non invasive tools are critically needed to improve early lung cancer detection and optimize primary care referral pathways. We e...
The opioid crisis has severely impacted Ohio, with overdose death rates surpassing national averages and disproportionately affecting rural and Appala...