AIMC Topic: Emergency Service, Hospital
Clear Filters Showing 181 to 190 of 462 articles
Hospital crowdedness evaluation and in-hospital resource allocation based on image recognition technology.
Scientific reports
Jan 6, 2023
How to allocate the existing medical resources reasonably, alleviate hospital congestion and improve the patient experience are problems faced by all hospitals. At present, the combination of artificial intelligence and the medical field is mainly in...
Decision Aids, Doorknob Moments, and Physician-Patient Solidarity in EDs.
AMA journal of ethics
Dec 1, 2022
Potential benefits of decision aids and technology, such as artificial intelligence, used at the bedside are many and significant. Like any tools, they must be used appropriately for specific tasks, since even validated decision aids have limited uti...
Artificial intelligence and machine learning on diagnosis and classification of hip fracture: systematic review.
Journal of orthopaedic surgery and research
Dec 1, 2022
BACKGROUND: In the emergency room, clinicians spend a lot of time and are exposed to mental stress. In addition, fracture classification is important for determining the surgical method and restoring the patient's mobility. Recently, with the help of...
Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients.
Scientific reports
Nov 15, 2022
Myocardial infarction diagnosis is a common challenge in the emergency department. In managed settings, deep learning-based models and especially convolutional deep models have shown promise in electrocardiogram (ECG) classification, but there is a l...
Prediction of anemia using facial images and deep learning technology in the emergency department.
Frontiers in public health
Nov 9, 2022
BACKGROUND: According to the WHO, anemia is a highly prevalent disease, especially for patients in the emergency department. The pathophysiological mechanism by which anemia can affect facial characteristics, such as membrane pallor, has been proven ...
A Natural Language Processing and Machine Learning Approach to Identification of Incidental Radiology Findings in Trauma Patients Discharged from the Emergency Department.
Annals of emergency medicine
Oct 31, 2022
STUDY OBJECTIVE: Patients undergoing diagnostic imaging studies in the emergency department (ED) commonly have incidental findings, which may represent unrecognized serious medical conditions, including cancer. Recognition of incidental findings freq...
Prediction of disorders with significant coronary lesions using machine learning in patients admitted with chest symptom.
PloS one
Oct 10, 2022
BACKGROUND: The early prediction of significant coronary artery lesion, including coronary vasospasm, have yet to be studied. It is essential to discern the disorders with significant coronary lesions (SCDs) requiring coronary angiography from mimick...
The Impact of Cultural Embeddedness on the Implementation of an Artificial Intelligence Program at Triage: A Qualitative Study.
Journal of transcultural nursing : official journal of the Transcultural Nursing Society
Oct 8, 2022
INTRODUCTION: Triage requires rapid determination of acuity and resources. Current modalities allow for individual judgment, with varied application of algorithmic rules. Although artificial intelligence can improve triage accuracy, gaps remain in un...
Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial.
Journal of medical Internet research
Sep 8, 2022
BACKGROUND: Frail older people use emergency services extensively, and digital systems that monitor health remotely could be useful in reducing these visits by earlier detection of worsening health conditions.
Imbalanced prediction of emergency department admission using natural language processing and deep neural network.
Journal of biomedical informatics
Aug 19, 2022
The emergency department (ED) plays a very significant role in the hospital. Owing to the rising number of ED visits, medical service points, and ED market, overcrowding of EDs has become serious worldwide. Overcrowding has long been recognized as a ...
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