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Emergency Treatment

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Robotic telepresence versus standardly supervised stroke alert team assessments.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association 25490742
BACKGROUND: Telemedicine has created access to emergency stroke care for patients in all communities, regardless of geography. We hypothesized that there is no difference in speed of assessment between vascular neurologist (VN) robotic telepresence a...
Adult Aged Aged, 80 and over Arizona Chi-Square Distribution Emergencies Emergency Treatment Endovascular Procedures Female Follow-Up Studies Humans Linear Models Male Middle Aged Risk Assessment Robotics Severity of Illness Index Stroke Survival Analysis Telemedicine Thrombolytic Therapy Time Factors Time-to-Treatment Treatment Outcome
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Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology.

European journal of emergency medicine : official journal of the European Society for Emergency Medicine 24509606
OBJECTIVE: Our objective was to apply neural network methodology to determine whether adding coded chief complaint (CCC) data to triage information would result in an improved hospital admission prediction model than one without CCC data.
Aged Aged, 80 and over Algorithms Area Under Curve Cohort Studies Confidence Intervals Emergency Medicine Emergency Service, Hospital Emergency Treatment Female Hospitalization Humans Male Neural Networks, Computer Patient Admission Pennsylvania Predictive Value of Tests Reproducibility of Results Retrospective Studies Risk Assessment Triage
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Emergency Department Capacity Planning: A Recurrent Neural Network and Simulation Approach.

Computational and mathematical methods in medicine 31827585
Emergency departments (EDs) play a vital role in the whole healthcare system as they are the first point of care in hospitals for urgent and critically ill patients. Therefore, effective management of hospital's ED is crucial in improving the quality...
Algorithms Bed Occupancy Climate Computer Simulation Emergency Service, Hospital Emergency Treatment Hospital Administration Humans Length of Stay Machine Learning Neural Networks, Computer Reproducibility of Results Time Factors Turkey
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Using Artificial Intelligence to Predict Surgical Shunts in Men with Ischemic Priapism.

The Journal of urology 32516073
PURPOSE: Ischemic priapism is a urological emergency that requires prompt intervention to preserve erectile function. Characteristics that influence escalation to surgical intervention remain unclear. We identified factors and developed machine learn...
Adolescent Adult Aged Aged, 80 and over Anastomosis, Surgical Emergency Service, Hospital Emergency Treatment Erectile Dysfunction Humans Likelihood Functions Machine Learning Male Middle Aged Models, Statistical Paracentesis Penile Erection Penis Phenylephrine Priapism Retrospective Studies Risk Assessment Time Factors Treatment Outcome Urologic Surgical Procedures, Male Young Adult
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Validation of the Artificial Intelligence-Based Predictive Optimal Trees in Emergency Surgery Risk (POTTER) Calculator in Emergency General Surgery and Emergency Laparotomy Patients.

Journal of the American College of Surgeons 33705983
BACKGROUND: The Predictive Optimal Trees in Emergency Surgery Risk (POTTER) tool is an artificial intelligence-based calculator for the prediction of 30-day outcomes in patients undergoing emergency operations. In this study, we sought to assess the ...
Adult Aged Artificial Intelligence Benchmarking Databases, Factual Decision Trees Emergency Service, Hospital Emergency Treatment Feasibility Studies Female Hospital Mortality Humans Laparotomy Male Middle Aged Postoperative Complications Risk Assessment Risk Factors
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Machine learning for outcome predictions of patients with trauma during emergency department care.

BMJ health & care informatics 34625448
OBJECTIVES: To develop and evaluate a machine learning model for predicting patient with trauma mortality within the US emergency departments.
Adult Child Emergency Service, Hospital Emergency Treatment Female Humans Machine Learning Male Prognosis Retrospective Studies
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The new SUMPOT to predict postoperative complications using an Artificial Neural Network.

Scientific reports 34811383
An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. This study aims at implementing an automated surgical risk calculator based on Artificial Neural Netw...
Area Under Curve Cohort Studies Elective Surgical Procedures Emergency Treatment Female Hospitalization Humans Intensive Care Units Machine Learning Male Middle Aged Neural Networks, Computer Postoperative Complications Predictive Value of Tests Prognosis Retrospective Studies Risk Assessment Risk Factors ROC Curve
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