AI Medical Compendium Topic

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Emergency Service, Hospital

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XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department.

Artificial intelligence in medicine
Nowadays it is increasingly important in many applications to understand how different factors influence a variable of interest in a predictive modeling process. This task becomes particularly important in the context of Explainable Artificial Intell...

Hospital crowdedness evaluation and in-hospital resource allocation based on image recognition technology.

Scientific reports
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
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
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
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
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
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
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...