In recent years, the omnipresence of cardiac problems has been recognized as an epidemic. With the correct and quick diagnosis, both mortality and morbidity from cardiac disorders can be dramatically reduced. However, frequent medical check-ups are p...
Neck contrast-enhanced CT (CECT) is a routine tool used to evaluate patients with cervical lymphadenopathy. This study aimed to evaluate the ability of convolutional neural networks (CNNs) to classify Kikuchi-Fujimoto's disease (KD) and cervical tube...
BACKGROUND: Currently, the risk stratification of critically ill patient with chest pain is a challenge. We aimed to use machine learning approach to predict the critical care outcomes in patients with chest pain, and simultaneously compare its perfo...
BACKGROUND: Chest pain is amongst the most common reason for presentation to the emergency department (ED). There are many causes of chest pain, and it is important for the emergency physician to quickly and accurately diagnose life threatening cause...
BACKGROUND: Self-reported symptoms during the COVID-19 pandemic have been used to train artificial intelligence models to identify possible infection foci. To date, these models have only considered the culmination or peak of symptoms, which is not s...
International journal of environmental research and public health
Feb 23, 2021
Thoracic pain is a shared symptom among gastrointestinal diseases, muscle pain, emotional disorders, and the most deadly: Cardiovascular diseases. Due to the limited space in the emergency department, it is important to identify when thoracic pain is...
Coronary artery calcium is an accurate predictor of cardiovascular events. While it is visible on all computed tomography (CT) scans of the chest, this information is not routinely quantified as it requires expertise, time, and specialized equipment....
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Anginal symptoms can connote increased cardiac risk and a need for change in cardiovascular management. In this study, a pre-trained transformer architecture was used to automatically detect and characterize anginal symptoms from within the history o...
Scandinavian journal of trauma, resuscitation and emergency medicine
Sep 11, 2020
BACKGROUND: A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest pain in ...
BACKGROUND: Computerised electrocardiogram (ECG) interpretation diagnostic algorithms have been developed to guide clinical decisions like with ST segment elevation myocardial infarction (STEMI) where time in decision making is critical. These comput...
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