Emergency Medicine

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

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Showing 1975-1995 of 5,252 articles
Early triage of critically ill COVID-19 patients using deep learning.

The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical il...

Development of machine learning models to prognosticate chronic shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage.

BACKGROUND: Shunt-dependent hydrocephalus significantly complicates subarachnoid hemorrhage (SAH), a...

The first use of artificial intelligence (AI) in the ER: triage not diagnosis.

Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting r...

Using trauma registry data to predict prolonged mechanical ventilation in patients with traumatic brain injury: Machine learning approach.

OBJECTIVES: We aimed to build a machine learning predictive model to predict the risk of prolonged m...

Artificial Intelligence and Machine Learning in Computational Nanotoxicology: Unlocking and Empowering Nanomedicine.

Advances in nanomedicine, coupled with novel methods of creating advanced materials at the nanoscale...

Review of different platforms to perform rapid onsite evaluation via telecytology.

There is increased utilisation of cytopathology to provide a rapid onsite evaluation (ROSE) of fine ...

Artificial intelligence method to classify ophthalmic emergency severity based on symptoms: a validation study.

OBJECTIVES: We investigated the usefulness of machine learning artificial intelligence (AI) in class...

Machine learning prediction of stone-free success in patients with urinary stone after treatment of shock wave lithotripsy.

BACKGROUND: The aims of this study were to determine the predictive value of decision support analys...

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients.

BACKGROUND/AIMS: Human grading of digital images from diabetic retinopathy (DR) screening programmes...

Agents and robots for collaborating and supporting physicians in healthcare scenarios.

Monitoring patients through robotics telehealth systems is an interesting scenario where patients' c...

Human-computer collaboration for skin cancer recognition.

The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligenc...

An Approach to Biomarker Discovery of Cannabis Use Utilizing Proteomic, Metabolomic, and Lipidomic Analyses.

Relatively little is known about the molecular pathways influenced by cannabis use in humans. We us...

Artificial intelligence and radiomics in pediatric molecular imaging.

In the past decade, a new approach for quantitative analysis of medical images and prognostic modell...

Predicting direct hepatocyte toxicity in humans by combining high-throughput imaging of HepaRG cells and machine learning-based phenotypic profiling.

Accurate prediction of drug- and chemical-induced hepatotoxicity remains to be a problem for pharmac...

Toward automatic C-arm positioning for standard projections in orthopedic surgery.

PURPOSE: Guidance and quality control in orthopedic surgery increasingly rely on intra-operative flu...

A novel model for predicting the outcome of intracerebral hemorrhage: Based on 1186 Patients.

OBJECTIVE: To establish a model for predicting the outcome according to the clinical and computed to...

Utilization of a Deep Learning Algorithm for Microscope-Based Fatty Vacuole Quantification in a Fatty Liver Model in Mice.

Quantification of fatty vacuoles in the liver, with differentiation from lumina of liver blood vesse...

Effectiveness of robot-assisted gait training on patients with burns: a preliminary study.

Gait enables individuals to move forward and is considered a natural skill. However, gait disturbanc...

Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach.

BACKGROUND: The use of machine learning techniques to predict diseases outcomes has grown significan...

Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review.

Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including...

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