AIMC Topic: Wounds and Injuries

Clear Filters Showing 141 to 150 of 160 articles

Early Identification of Trauma-induced Coagulopathy: Development and Validation of a Multivariable Risk Prediction Model.

Annals of surgery Dec 1, 2021
OBJECTIVE: The aim of this study was to develop and validate a risk prediction tool for trauma-induced coagulopathy (TIC), to support early therapeutic decision-making.
Adult Male Middle Aged Risk Assessment Clinical Decision-Making Female Aged Aged, 80 and over Blood Coagulation Disorders Wounds and Injuries London Trauma Severity Indices Adolescent Predictive Value of Tests Bayes Theorem Supervised Machine Learning Humans Prospective Studies
View on PubMed DOI

Enhancing Military Burn- and Trauma-Related Acute Kidney Injury Prediction Through an Automated Machine Learning Platform and Point-of-Care Testing.

Archives of pathology & laboratory medicine Mar 1, 2021
CONTEXT.—: Delayed recognition of acute kidney injury (AKI) results in poor outcomes in military and civilian burn-trauma care. Poor predictive ability of urine output (UOP) and creatinine contribute to the delayed recognition of AKI.
Humans Machine Learning Algorithms Biomarkers Point-of-Care Testing Lipocalin-2 Burns Adult Creatinine Male Military Personnel Middle Aged Wounds and Injuries Predictive Value of Tests Acute Kidney Injury Female Aged Aged, 80 and over
View on PubMed DOI

A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit.

The journal of trauma and acute care surgery Oct 1, 2020
BACKGROUND: Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We...
ROC Curve Sodium Critical Care Proportional Hazards Models Adult Male Middle Aged Sepsis Multivariate Analysis Injury Severity Score Organ Dysfunction Scores Wounds and Injuries Machine Learning Prognosis Retrospective Studies Critical Illness Intensive Care Units Female Hospitalization Young Adult Humans Neural Networks, Computer
View on PubMed DOI

Dynamic impact of transfusion ratios on outcomes in severely injured patients: Targeted machine learning analysis of the Pragmatic, Randomized Optimal Platelet and Plasma Ratios randomized clinical trial.

The journal of trauma and acute care surgery Sep 1, 2020
BACKGROUND: Massive transfusion protocols to treat postinjury hemorrhage are based on predefined blood product transfusion ratios followed by goal-directed transfusion based on patient's clinical evolution. However, it remains unclear how these trans...
Machine Learning Female Male Hemorrhage Erythrocytes Blood Platelets Plasma Blood Component Transfusion Humans Trauma Centers Intention to Treat Analysis Wounds and Injuries Hemostasis North America
View on PubMed DOI

Assessment of a Deep Learning Algorithm for the Detection of Rib Fractures on Whole-Body Trauma Computed Tomography.

Korean journal of radiology Jul 1, 2020
OBJECTIVE: To assess the diagnostic performance of a deep learning-based algorithm for automated detection of acute and chronic rib fractures on whole-body trauma CT.
Humans Rib Fractures Retrospective Studies Tomography, X-Ray Computed Female Aged Image Interpretation, Computer-Assisted Wounds and Injuries Whole Body Imaging Adult Male Middle Aged Deep Learning
View on PubMed DOI

Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.

The journal of trauma and acute care surgery May 1, 2020
BACKGROUND: Incomplete prehospital trauma care is a significant contributor to preventable deaths. Current databases lack timelines easily constructible of clinical events. Temporal associations and procedural indications are critical to characterize...
Pilot Projects Emergency Medical Services Natural Language Processing Quality Improvement Humans Electronic Health Records Quality Assurance, Health Care Wounds and Injuries
View on PubMed DOI

Intelligence in injury prevention: artificial and otherwise.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention Feb 1, 2020
Humans Artificial Intelligence Wounds and Injuries Satellite Imagery Accident Prevention
View on PubMed DOI

A Machine Learning-Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis Jan 1, 2020
Acute traumatic coagulopathy (ATC) is an extremely common but silent murderer; this condition presents early after trauma and impacts approximately 30% of severely injured patients who are admitted to emergency departments (EDs). Given that conventio...
Adult Male Middle Aged Risk Assessment Machine Learning Algorithms Female Hospitalization Wounds and Injuries Emergencies Predictive Value of Tests International Normalized Ratio Blood Coagulation Disorders Humans
View on PubMed DOI

Data-driven specialisation of wound care through artificial intelligence.

International wound journal Aug 1, 2019
Humans Artificial Intelligence Delivery of Health Care Inventions Wounds and Injuries Decision Making, Computer-Assisted
View on PubMed DOI

Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: A multicenter study.

The journal of trauma and acute care surgery Jul 1, 2019
BACKGROUND: Trauma has long been considered unpredictable. Artificial neural networks (ANN) have recently shown the ability to predict admission volume, acuity, and operative needs at a single trauma center with very high reliability. This model has ...
Geography, Medical Bayes Theorem Injury Severity Score Wounds and Injuries Humans Trauma Centers Neural Networks, Computer United States
View on PubMed DOI
Popular Topics
Recent Journals