AIMC Topic: Emergency Service, Hospital

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Potentially inappropriate polypharmacy is an important predictor of 30-day emergency hospitalisation in older adults: a machine learning feature validation study.

Age and ageing May 31, 2025
BACKGROUND: Machine learning (ML) models in healthcare are crucial for predicting clinical outcomes, and their effectiveness can be significantly enhanced through improvements in accuracy, generalisability, and interpretability. To achieve widespread...
Aged, 80 and over Male Risk Assessment Risk Factors Hospitalization Aged Geriatric Assessment United Kingdom Polypharmacy Inappropriate Prescribing Time Factors Age Factors Emergency Service, Hospital Female Reproducibility of Results Humans Machine Learning Potentially Inappropriate Medication List
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Artificial intelligence applied to electrocardiogram to rule out acute myocardial infarction: the ROMIAE multicentre study.

European heart journal May 21, 2025
BACKGROUND AND AIMS: Emerging evidence supports artificial intelligence-enhanced electrocardiogram (AI-ECG) for detecting acute myocardial infarction (AMI), but real-world validation is needed. The aim of this study was to evaluate the performance of...
Electrocardiography Emergency Service, Hospital Myocardial Infarction Aged Male Middle Aged Prospective Studies Republic of Korea Female Humans Artificial Intelligence
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Clinical Requirements for Transparent Machine Learning Model Information: A Mixed Methods Study Protocol.

Studies in health technology and informatics May 15, 2025
Limited transparency of machine learning models poses risks their effective use. Through semi-structured interviews with physicians, this mixed methods study will qualitatively identify requirements for transparent machine learning model information ...
Humans Machine Learning Decision Support Systems, Clinical Emergency Service, Hospital
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Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project.

Studies in health technology and informatics May 15, 2025
The PERMANENS European project addresses the global public health challenge of self-harm and suicide by developing a machine learning-based Clinical Decision Support System (CDSS) to assist emergency departments (EDs) in providing personalized care. ...
Decision Support Systems, Clinical Europe Emergency Service, Hospital Risk Management Humans Machine Learning Suicide Prevention
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A meta-analysis of the diagnostic test accuracy of artificial intelligence predicting emergency department dispositions.

BMC medical informatics and decision making May 15, 2025
BACKGROUND: The rapid advancement of Artificial Intelligence (AI) has led to its widespread application across various domains, showing encouraging outcomes. Many studies have utilized AI to forecast emergency department (ED) disposition, aiming to f...
Humans Artificial Intelligence Emergency Service, Hospital Diagnostic Tests, Routine
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Artificial intelligence for severity triage based on conversations in an emergency department in Korea.

Scientific reports May 15, 2025
In the fast-paced emergency departments, where crises unfold unpredictably, the systematic prioritization of critical patients based on a severity classification is vital for swift and effective treatment. This study aimed to enhance the quality of e...
ROC Curve Neural Networks, Computer Support Vector Machine Female Artificial Intelligence Natural Language Processing Triage Machine Learning Emergency Service, Hospital Humans Male Algorithms Severity of Illness Index Republic of Korea
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Predicting sepsis treatment decisions in the paediatric emergency department using machine learning: the AiSEPTRON study.

BMJ paediatrics open May 14, 2025
BACKGROUND: Early identification of children at risk of sepsis in emergency departments (EDs) is crucial for timely treatment and improved outcomes. Existing risk scores and criteria for paediatric sepsis are not well-suited for early diagnosis in ED...
Triage Emergency Service, Hospital United Kingdom Female Male Infant Anti-Bacterial Agents Humans Retrospective Studies Child, Preschool Machine Learning Sepsis Clinical Decision-Making Child Adolescent
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[A new artificial intelligence tool for assessing symptoms in patients seeking emergency department care: the Mediktor application].

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias May 13, 2025
OBJECTIVES: To analyze agreement between diagnoses issued by the Mediktor application and those of an attending physician, and to evaluate the usefulness of this application in patients who seek emergency care.
Middle Aged Surveys and Questionnaires Decision Support Systems, Clinical Adult Humans Double-Blind Method Clinical Decision-Making Mobile Applications Aged Sensitivity and Specificity Hospitals, University Artificial Intelligence Diagnosis, Differential Male Female Tertiary Care Centers Prospective Studies Emergency Service, Hospital Aged, 80 and over Computers, Handheld
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AI-Enhanced Speech Recognition in Triage.

Studies in health technology and informatics May 2, 2025
Triage is used in emergency departments to ensure timely patient care according to urgency of treatment. However, triage accuracy and efficiency remain challenging due to time-constraints and high demand. This proof-of-concept study evaluates an AI-p...
Emergency Service, Hospital Switzerland Speech Recognition Software Humans Artificial Intelligence Triage
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AI-Based Analysis of Abdominal Ultrasound Images to Support Medical Diagnosis in Emergency Departments.

Studies in health technology and informatics May 2, 2025
The goal of segmentation in abdominal imaging for emergency medicine is to accurately identify and delineate organs, as well as to detect and localize pathological areas. This precision is critical for rapid, informed decision-making in acute care sc...
Abdomen Emergency Service, Hospital Image Interpretation, Computer-Assisted Humans Artificial Intelligence Ultrasonography
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