Deep learning algorithms have shown excellent performances in the field of medical image recognition, and practical applications have been made in several medical domains. Little is known about the feasibility and impact of an undetectable adversaria...
AIMS: Our aim was to evaluate the performance of machine learning (ML), integrating clinical parameters with coronary artery calcium (CAC), and automated epicardial adipose tissue (EAT) quantification, for the prediction of long-term risk of myocardi...
OBJECTIVES: Early detection of sepsis is critical in clinical practice since each hour of delayed treatment has been associated with an increase in mortality due to irreversible organ damage. This study aimed to develop an explainable artificial inte...
OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results ...
Journal of thrombosis and thrombolysis
Nov 1, 2020
The pandemic of coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. During this time, the management of people with acute coronary syndromes (ACS) and COVID-19 has become a global issue, especially since...
Journal of the American College of Cardiology
Oct 6, 2020
BACKGROUND: Clinical practice guidelines recommend assessment of subclinical atherosclerosis using imaging techniques in individuals with intermediate atherosclerotic cardiovascular risk according to standard risk prediction tools.
Suicide poses a significant health burden worldwide. In many cases, people at risk of suicide do not engage with their doctor or community due to concerns about stigmatisation and forced medical treatment; worse still, people with mental illness (wh...
Current opinion in endocrinology, diabetes, and obesity
Oct 1, 2020
PURPOSE OF REVIEW: Current methods for thyroid nodule risk stratification are subjective, and artificial intelligence algorithms have been used to overcome this shortcoming. In this review, we summarize recent developments in the application of artif...
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Oct 1, 2020
OBJECTIVES: To develop a machine-learning (ML) model for prediction of shoulder dystocia (ShD) and to externally validate the model's predictive accuracy and potential clinical efficacy in optimizing the use of Cesarean delivery in the context of sus...
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