AIMC Topic: Emergency Service, Hospital
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Enhancing pneumonia prognosis in the emergency department: a novel machine learning approach using complete blood count and differential leukocyte count combined with CURB-65 score.
BMC medical informatics and decision making
May 3, 2024
BACKGROUND: Pneumonia poses a major global health challenge, necessitating accurate severity assessment tools. However, conventional scoring systems such as CURB-65 have inherent limitations. Machine learning (ML) offers a promising approach for pred...
Development of a Predictive Model for Survival Over Time in Patients With Out-of-Hospital Cardiac Arrest Using Ensemble-Based Machine Learning.
Computers, informatics, nursing : CIN
May 1, 2024
As of now, a model for predicting the survival of patients with out-of-hospital cardiac arrest has not been established. This study aimed to develop a model for identifying predictors of survival over time in patients with out-of-hospital cardiac arr...
Emergency department risk model: timely identification of patients for outpatient care coordination.
The American journal of managed care
May 1, 2024
OBJECTIVE: Major depressive disorder (MDD) is linked to a 61% increased risk of emergency department (ED) visits and frequent ED usage. Collaborative care management (CoCM) models target MDD treatment in primary care, but how best to prioritize patie...
Artificial Intelligence for Emergency Care Triage-Much Promise, but Still Much to Learn.
JAMA network open
May 1, 2024
Preclinical identification of acute coronary syndrome without high sensitivity troponin assays using machine learning algorithms.
Scientific reports
Apr 29, 2024
Preclinical management of patients with acute chest pain and their identification as candidates for urgent coronary revascularization without the use of high sensitivity troponin essays remains a critical challenge in emergency medicine. We enrolled ...
An ensemble model for predicting dispositions of emergency department patients.
BMC medical informatics and decision making
Apr 22, 2024
OBJECTIVE: The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning's potential to predict ED disposit...
Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.
BMJ health & care informatics
Apr 22, 2024
BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has...
Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels.
Emergency medicine journal : EMJ
Apr 22, 2024
BACKGROUND: Tools to increase the turnaround speed and accuracy of imaging reports could positively influence ED logistics. The Caire ICH is an artificial intelligence (AI) software developed for ED physicians to recognise intracranial haemorrhages (...
How artificial intelligence could transform emergency care.
The American journal of emergency medicine
Apr 16, 2024
Artificial intelligence (AI) in healthcare is the ability of a computer to perform tasks typically associated with clinical care (e.g. medical decision-making and documentation). AI will soon be integrated into an increasing number of healthcare appl...
Identifying signs and symptoms of urinary tract infection from emergency department clinical notes using large language models.
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Apr 3, 2024
BACKGROUND: Natural language processing (NLP) tools including recently developed large language models (LLMs) have myriad potential applications in medical care and research, including the efficient labeling and classification of unstructured text su...
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