AIMC Topic: Wounds and Injuries

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Virtual Wound Care in Australian Nursing Homes: Protocol for a Pilot and Feasibility Study.

JMIR research protocols
BACKGROUND: Chronic wounds, those which have not healed in a timely manner, are a significant health and economic burden. Older people, especially those living in nursing homes, are disproportionately affected by chronic wounds, and effective managem...

Higher hospital level does not improve 30-day survival after road traffic accidents.

Scientific reports
Globally, road traffic accidents (RTAs) remain a major cause of death, particularly among individuals aged 15-30 years. While Sweden has been at the forefront of traffic safety through the Vision Zero initiative, in-hospital management remains crucia...

Road traffic injuries (RTIs) in children and adolescents in India: an overview of epidemiology, reported reasons and its implications.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
INTRODUCTION: Road traffic injuries (RTIs) rank among the top causes of mortality and disability in children and adolescents, resulting in substantial socioeconomic impacts.

Virtual case reasoning and AI-assisted diagnostic instruction: an empirical study based on body interact and large language models.

BMC medical education
BACKGROUND: Integrating large language models (LLMs) with virtual patient platforms offers a novel approach to teaching clinical reasoning. This study evaluated the performance and educational value of combining Body Interact with two AI models, Chat...

MIASurviveMTP: Machine learning for immediate assessment and survival prediction after massive transfusion protocol.

PloS one
Early triage of trauma patients requiring massive transfusion (MT) may help to marshal appropriate resources and improve treatment and outcome. Artificial intelligence (AI) and machine learning (ML) offer theoretical advantages compared to convention...

Prognostic value of admission ROTEM in trauma: enhancing 30-day all-cause mortality prediction using machine learning.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
BACKGROUND: Haemorrhage is a leading cause of trauma death, yet early coagulation markers are rarely used to predict long-term outcomes. This study assessed whether a single admission rotational thromboelastometry (ROTEM) test could independently pre...

Deep Learning-based Gait Recognition and Evaluation of the Wounded.

Disaster medicine and public health preparedness
OBJECTIVES: Remote injury assessment during natural disasters poses major challenges for healthcare providers due to the inaccessibility of disaster sites. This study aimed to explore the feasibility of using artificial intelligence (AI) techniques f...

Early clinical evaluation of a machine-learning system for risk prediction of trauma-induced coagulopathy in the prehospital setting.

Emergency medicine journal : EMJ
BACKGROUND: Early intervention in patients with major traumatic injuries is critical. Decision support can improve clinicians' ability to identify high-risk patients. The aim of this study was to compare the performance of a machine-learning (ML) dec...

Predictors of Anemia Intolerance for Real-Time Transfusion Decision-Making During Resuscitation of Trauma Subjects: A Machine Learning Approach Using Heart Rate Variability.

Critical care explorations
OBJECTIVES: RBC transfusion in anemic patients with sustainable tolerance may cause harm, emphasizing the need for reliable metrics that quantify adequacy (oxygen delivery ≥ demand) and sustainability (oxygen delivery remains adequate without transfu...

Comparative evaluation of deep learning and traditional models for predicting traffic accident severity in Saudi Arabia.

Scientific reports
Road traffic accidents are one of the leading death causes around the globe, claiming millions of lives every year. Predicting traffic accident severity is essential for road users' safety and accident prevention. Artificial neural network (ANN), Boo...