AIMC Topic: Triage

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A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support system.

Scientific reports
The array of complex and evolving patient data has limited clinical decision making in the emergency department (ED). This study introduces an advanced deep learning algorithm designed to enhance real-time prediction accuracy for integration into a n...

The use of artificial intelligence based chat bots in ophthalmology triage.

Eye (London, England)
PURPOSE: To evaluate AI-based chat bots ability to accurately answer common patient's questions in the field of ophthalmology.

Machine learning outperforms the Canadian Triage and Acuity Scale (CTAS) in predicting need for early critical care.

CJEM
STUDY OBJECTIVE: This study investigates the potential to improve emergency department (ED) triage using machine learning models by comparing their predictive performance with the Canadian Triage Acuity Scale (CTAS) in identifying the need for critic...

Application of artificial intelligence in triage in emergencies and disasters: a systematic review.

BMC public health
INTRODUCTION AND OBJECTIVE: Modern and intelligent triage systems are used today due to the growing trend of disasters and emergencies worldwide and the increase in the number of injured people facing the challenge of using traditional triage methods...

Improving triage performance in emergency departments using machine learning and natural language processing: a systematic review.

BMC emergency medicine
BACKGROUND: In Emergency Departments (EDs), triage is crucial for determining patient severity and prioritizing care, typically using the Manchester Triage Scale (MTS). Traditional triage systems, reliant on human judgment, are prone to under-triage ...

Exploring the potential of artificial intelligence models for triage in the emergency department.

Postgraduate medicine
OBJECTIVE: To perform a comparative analysis of the three-level triage protocol conducted by triage nurses and emergency medicine doctors with the use of ChatGPT, Gemini, and Pi, which are recognized artificial intelligence (AI) models widely used in...

Real-World evaluation of an AI triaging system for chest X-rays: A prospective clinical study.

European journal of radiology
Chest X-rays (CXRs) are crucial for diagnosing and managing lung conditions. While CXR is a common and cost-effective diagnostic tool, interpreting the high volume of CXRs is challenging due to workforce limitations. Artificial intelligence (AI) offe...

Analysis of ChatGPT in the Triage of Common Spinal Complaints.

World neurosurgery
BACKGROUND: ChatGPT is a natural language processing chatbot with a significant prevalence in modern media with a clear application in the medical triage workflow. ChatGPT has shown significant capacity for understanding clinical vignettes, radiology...

Enhancing Performance of the National Field Triage Guidelines Using Machine Learning: Development of a Prehospital Triage Model to Predict Severe Trauma.

Journal of medical Internet research
BACKGROUND: Prehospital trauma triage is essential to get the right patient to the right hospital. However, the national field triage guidelines proposed by the American College of Surgeons have proven to be relatively insensitive when identifying se...

A large language model-based clinical decision support system for syncope recognition in the emergency department: A framework for clinical workflow integration.

European journal of internal medicine
Differentiation of syncope from transient loss of consciousness can be challenging in the emergency department (ED). Natural Language Processing (NLP) enables the analysis of free text in the electronic medical records (EMR). The present paper aimed ...