AIMC Topic: Emergency Service, Hospital
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Machine learning-based prediction of critical illness in children visiting the emergency department.
PloS one
Feb 17, 2022
OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have ...
A joint convolutional-recurrent neural network with an attention mechanism for detecting intracranial hemorrhage on noncontrast head CT.
Scientific reports
Feb 8, 2022
To investigate the performance of a joint convolutional neural networks-recurrent neural networks (CNN-RNN) using an attention mechanism in identifying and classifying intracranial hemorrhage (ICH) on a large multi-center dataset; to test its perform...
Artificial Intelligence Technology-Based Medical Information Processing and Emergency First Aid Nursing Management.
Computational and mathematical methods in medicine
Feb 4, 2022
This study was aimed at exploring the new management mode of medical information processing and emergency first aid nursing management under the new artificial intelligence technology. This study will use the artificial intelligence algorithm to opti...
Using the Social Robot NAO for Emotional Support to Children at a Pediatric Emergency Department: Randomized Clinical Trial.
Journal of medical Internet research
Jan 13, 2022
BACKGROUND: Social robots (SRs) have been used for improving anxiety in children in stressful clinical situations, such as during painful procedures. However, no studies have yet been performed to assess their effect in children while waiting for eme...
A 12-hospital prospective evaluation of a clinical decision support prognostic algorithm based on logistic regression as a form of machine learning to facilitate decision making for patients with suspected COVID-19.
PloS one
Jan 5, 2022
OBJECTIVE: To prospectively evaluate a logistic regression-based machine learning (ML) prognostic algorithm implemented in real-time as a clinical decision support (CDS) system for symptomatic persons under investigation (PUI) for Coronavirus disease...
A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation.
Journal of medical Internet research
Jan 3, 2022
BACKGROUND: Detection and quantification of intra-abdominal free fluid (ie, ascites) on computed tomography (CT) images are essential processes for finding emergent or urgent conditions in patients. In an emergency department, automatic detection and...
A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study.
Journal of medical Internet research
Dec 27, 2021
BACKGROUND: Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a triage system, such as the 5-level emergency severity index, somewhat improves the process of ED treat...
Development and validation of a practical machine-learning triage algorithm for the detection of patients in need of critical care in the emergency department.
Scientific reports
Dec 15, 2021
Identifying critically ill patients is a key challenge in emergency department (ED) triage. Mis-triage errors are still widespread in triage systems around the world. Here, we present a machine learning system (MLS) to assist ED triage officers bette...
Using explainable machine learning to characterise data drift and detect emergent health risks for emergency department admissions during COVID-19.
Scientific reports
Nov 26, 2021
A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and aids organisational planning. Supervised machine learning algorithms can use data describing historic...
Development and validation of a sensitive and high throughput UPLC-MS/MS method for determination of paraquat and diquat in human plasma and urine: application to poisoning cases at emergency departments of hospitals.
Forensic toxicology
Nov 12, 2021
PURPOSE: Paraquat and diquat are well-known toxic herbicides, at least responsible for hundreds of fatal poisoning events worldwide. However, the determination of diquat and paraquat in plasma and urine is very challenging because of their high polar...
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