Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. A total of 1,730 peritoneal dialysis patients in the CRC for ESRD prospective cohort from 2008 to 20...
To assess the microcirculation in a patient's capillaries, clinicians often use the valuable and non-invasive diagnostic tool of nailfold capillaroscopy (NC). In particular, evaluating the images that result from NC is particularly important for diag...
OBJECTIVE: We analyzed data from inpatients with diabetes admitted to a large university hospital to predict the risk of hypoglycemia through the use of machine learning algorithms.
AJR. American journal of roentgenology
Apr 29, 2020
The purpose of this study was to assess, by analyzing features of the primary tumor with F-FDG PET, the utility of deep machine learning with a convolutional neural network (CNN) in predicting the potential of newly diagnosed non-small cell lung can...
PURPOSE: Patient age has important clinical utility for refining a differential diagnosis in radiology. Here, we evaluate the potential for convolutional neural network models to predict patient age based on anterior-posterior chest radiographs for i...
BACKGROUND: Nonophthalmologist physicians do not confidently perform direct ophthalmoscopy. The use of artificial intelligence to detect papilledema and other optic-disk abnormalities from fundus photographs has not been well studied.