Cardiovascular imaging is going to change substantially in the next decade, fueled by the deep learning revolution. For medical professionals, it is important to keep track of these developments to ensure that deep learning can have meaningful impact...
OBJECTIVES: This study sought to develop and compare an array of machine learning methods to predict in-hospital mortality after transcatheter aortic valve replacement (TAVR) in the United States.
Access to big data analyzed by supercomputers using advanced mathematical algorithms (i.e., deep machine learning) has allowed for enhancement of cognitive output (i.e., visual imaging interpretation) to previously unseen levels and promises to funda...
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Jul 1, 2019
OBJECTIVE: To evaluate the application of artificial intelligence (AI), i.e. deep learning and other machine-learning techniques, to amniotic fluid (AF) metabolomics and proteomics, alone and in combination with sonographic, clinical and demographic ...
BACKGROUND: Hospital length of stay (LOS) is an important quality metric for total hip arthroplasty. Accurately predicting LOS is important to expectantly manage bed utilization and other hospital resources. We aimed to develop a predictive model for...
To compare results for radiological prediction of pathological invasiveness in lung adenocarcinoma between radiologists and a deep learning (DL) system.Ninety patients (50 men, 40 women; mean age, 66 years; range, 40-88 years) who underwent pre-opera...
Clinical orthopaedics and related research
Jun 1, 2019
BACKGROUND: Identifying patients at risk of not achieving meaningful gains in long-term postsurgical patient-reported outcome measures (PROMs) is important for improving patient monitoring and facilitating presurgical decision support. Machine learni...
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