AI Medical Compendium Topic

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Emergency Medical Services

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A prehospital diagnostic algorithm for strokes using machine learning: a prospective observational study.

Scientific reports
High precision is optimal in prehospital diagnostic algorithms for strokes and large vessel occlusions. We hypothesized that prehospital diagnostic algorithms for strokes and their subcategories using machine learning could have high predictive value...

Characterizing Opioid Overdoses Using Emergency Medical Services Data : A Case Definition Algorithm Enhanced by Machine Learning.

Public health reports (Washington, D.C. : 1974)
OBJECTIVES: Tracking nonfatal overdoses in the escalating opioid overdose epidemic is important but challenging. The objective of this study was to create an innovative case definition of opioid overdose in North Carolina emergency medical services (...

Predicting outcomes after trauma: Prognostic model development based on admission features through machine learning.

Medicine
In an overcrowded emergency department (ED), trauma surgeons and emergency physicians need an accurate prognostic predictor for critical decision-making involving patients with severe trauma. We aimed to develope a machine learning-based early progno...

Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction.

Journal of healthcare engineering
This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multiscale sampling frequency of multisource heterogeneous data. The proposed model also demonstrates its su...

Clinical decision support for severe trauma patients: Machine learning based definition of a bundle of care for hemorrhagic shock and traumatic brain injury.

The journal of trauma and acute care surgery
BACKGROUND: Deviation from guidelines is frequent in emergency situations, and this may lead to increased mortality. Probably because of time constraints, 55% is the greatest reported guidelines compliance rate in severe trauma patients. This study a...

Artificial intelligence and machine learning for hemorrhagic trauma care.

Military Medical Research
Artificial intelligence (AI), a branch of machine learning (ML) has been increasingly employed in the research of trauma in various aspects. Hemorrhage is the most common cause of trauma-related death. To better elucidate the current role of AI and c...

Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care.

World journal of emergency surgery : WJES
Artificial intelligence (AI) and machine learning describe a broad range of algorithm types that can be trained based on datasets to make predictions. The increasing sophistication of AI has created new opportunities to apply these algorithms within ...

Ethical Perspectives on Implementing AI to Predict Mortality Risk in Emergency Department Patients: A Qualitative Study.

Studies in health technology and informatics
Artificial intelligence (AI) is predicted to improve health care, increase efficiency and save time and recourses, especially in the context of emergency care where many critical decisions are made. Research shows the urgent need to develop principle...

Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis.

The western journal of emergency medicine
Social determinants of health (SDoH) are known to impact the health and well-being of patients. However, information regarding them is not always collected in healthcare interactions, and healthcare professionals are not always well-trained or equip...