Emergency Medicine

Latest AI and machine learning research in emergency medicine for healthcare professionals.

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Showing 526-546 of 5,218 articles
Artificial intelligence in risk prediction and diagnosis of vertebral fractures.

With the increasing prevalence of vertebral fractures, accurate diagnosis and prognostication are es...

An explainable and supervised machine learning model for prediction of red blood cell transfusion in patients during hip fracture surgery.

AIM: The study aimed to develop a predictive model with machine learning (ML) algorithm, to predict ...

Identification of Potential Drug Targets for the Treatment of Severe Burn Wounds from a Multi-Omics Perspective.

PURPOSE: Severe burns result in significant skin damage, impairing its primary role as an infection ...

Photonic platform coupled with machine learning algorithms to detect pyrolysis products of crack cocaine in saliva: A proof-of-concept animal study.

The non-invasive detection of crack/cocaine and other bioactive compounds from its pyrolysis in sali...

Enhanced forecasting of emergency department patient arrivals using feature engineering approach and machine learning.

BACKGROUND: Emergency department (ED) overcrowding is an important problem in many countries. Accura...

Using machine learning and natural language processing in triage for prediction of clinical disposition in the emergency department.

BACKGROUND: Accurate triage is required for efficient allocation of resources and to decrease patien...

Lymphoma triage from H&E using AI for improved clinical management.

AIMS: In routine diagnosis of lymphoma, initial non-specialist triage is carried out when the sample...

Artificial intelligence in triage of COVID-19 patients.

In 2019, COVID-19 began one of the greatest public health challenges in history, reaching pandemic s...

Spontaneous Hepatic Rupture Complicating Preeclampsia and HELLP Syndrome: A Case Report.

Spontaneous hepatic rupture is a rare complication that occurs in pregnant mothers with HELLP syndr...

SMART: Development and Application of a Multimodal Multi-organ Trauma Screening Model for Abdominal Injuries in Emergency Settings.

RATIONALE AND OBJECTIVES: Effective trauma care in emergency departments necessitates rapid diagnosi...

Large Language Models Applied to Health Care Tasks May Improve Clinical Efficiency, Value of Care Rendered, Research, and Medical Education.

Large language models (LLMs) are generative artificial intelligence models that create content on th...

Diagnostic performance of neural network algorithms in skull fracture detection on CT scans: a systematic review and meta-analysis.

BACKGROUND AND AIM: The potential intricacy of skull fractures as well as the complexity of underlyi...

Development of a machine learning model for prediction of intraventricular hemorrhage in premature neonates.

PURPOSE: Intraventricular hemorrhage (IVH) is a common and severe complication in premature neonates...

Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions.

Diagnostic errors in health care pose significant risks to patient safety and are disturbingly commo...

Study on the application of deep learning artificial intelligence techniques in the diagnosis of nasal bone fracture.

PURPOSE: To evaluate the identification of nasal bone fractures and their clinical diagnostic signif...

A quality assessment tool for focused abdominal sonography for trauma examinations using artificial intelligence.

BACKGROUND: Current tools to review focused abdominal sonography for trauma (FAST) images for qualit...

Empowering cancer prevention with AI: unlocking new frontiers in prediction, diagnosis, and intervention.

Artificial intelligence is rapidly changing our world at an exponential rate and its transformative ...

Artificial intelligence in emergency neuroradiology: Current applications and perspectives.

Emergency neuroradiology provides rapid diagnostic decision-making and guidance for management for a...

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