Latest AI and machine learning research in emergency medicine for healthcare professionals.
Children are rarely affected by medical emergencies. The experience of doctors or paramedics with ch...
For the safety assessment of pharmaceuticals, initial data management requires accurate toxicologica...
UNLABELLED: In children, accidental injuries (AI) are the most common cause of major trauma. Althoug...
In the course of digitalization it is becoming increasingly rare for medical documents to be handwri...
BACKGROUND AND AIMS: The effect of vitamin C on vasopressor requirement in critically ill patients h...
PURPOSE: Patients undergoing radiotherapy (RT) or chemoradiotherapy (CRT) may require emergency depa...
A 57-year-old man visited our hospital with right hypochondralgia. Abdominal contrast CT showed a 10...
CONTEXT: Tsothel, a traditional Tibetan medicine, is regarded as 'the king of essences'. Nevertheles...
Assessment of the volume status by blood pressure (BP) monitoring is difficult, since baroreflex con...
INTRODUCTION: Most risk assessment tools assume that the impact of risk factors is linear and cumula...
Earlier we created a chemical hazard database via natural language processing of dossiers submitted ...
The intrinsic relationship between fluid volume and open wound size (%) has not been previously exam...
BACKGROUND: The goal of this study was to integrate temporal and weather data in order to create an ...
OBJECTIVES: Early prediction of undesired outcomes among newly hospitalized patients could improve p...
The purpose of this study was to use natural language processing of physician documentation to predi...
Initial results are reported on automated detection of intracranial hemorrhage from CT, which would ...
Machine learning techniques have been recently applied for discriminating between Viable and Non-Via...
To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to c...
Purpose Resilience engineering, job satisfaction and patient satisfaction were evaluated and analyze...
Artificial intelligence has been able to automatically learn and judge large-scale data to some exte...
In this paper, we propose a structural framework for population-based cancer epidemiology and evalua...