AIMC Topic: Emergencies

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Trauma outcome predictor: An artificial intelligence interactive smartphone tool to predict outcomes in trauma patients.

The journal of trauma and acute care surgery
BACKGROUND: Classic risk assessment tools often treat patients' risk factors as linear and additive. Clinical reality suggests that the presence of certain risk factors can alter the impact of other factors; in other words, risk modeling is not linea...

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
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...

Resilience actions to counteract the effects of climate change and health emergencies in cities: the role of artificial neural networks.

Annali dell'Istituto superiore di sanita
Both the World Health Organization (WHO) with its 2015 "Climate and Health Country Profile Project" and the Istituto Superiore di Sanità (ISS) with its 2018 "Health and Climate Change", agree on the emergency generated by the climate change and conce...

Evaluation of Depth Cameras for Use as an Augmented Reality Emergency Ruler.

Studies in health technology and informatics
Children are rarely affected by medical emergencies. The experience of doctors or paramedics with child emergencies is correspondingly poor. The anatomical features and individual calculations make such an emergency much more error-prone than a compa...

Surgical Risk Is Not Linear: Derivation and Validation of a Novel, User-friendly, and Machine-learning-based Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) Calculator.

Annals of surgery
INTRODUCTION: Most risk assessment tools assume that the impact of risk factors is linear and cumulative. Using novel machine-learning techniques, we sought to design an interactive, nonlinear risk calculator for Emergency Surgery (ES).