To describe perioperative outcomes following robot-assisted prostatectomy performed by a single surgeon during transitions between da Vinci standard/Si/Xi and the single port. Perioperative data were retrospectively evaluated of the first 40 consecut...
We hypothesized that imaging-only-based machine learning algorithms can analyze non-enhanced CT scans of patients with acute intracerebral hemorrhage (ICH). This retrospective multicenter cohort study analyzed 520 non-enhanced CT scans and clinical d...
BACKGROUND: We aimed to evaluate a deep learning (DL) model combining perinodular and intranodular radiomics features and clinical features for preoperative differentiation of solitary granuloma nodules (GNs) from solid lung cancer nodules in patient...
PURPOSE: We aimed to develop a deep learning (DL)-based algorithm for automated quantification of aortic valve calcium (AVC) from non-enhanced electrocardiogram-gated cardiac CT scans and compare performance of DL-measured AVC volume and Agatston sco...
BACKGROUND: Intraoperative hypotension is associated with a risk of postoperative organ dysfunction. In this study, we aimed to present deep learning algorithms for real-time predictions 5, 10, and 15 min before a hypotensive event.
PURPOSE: Convolutional neural networks (CNNs) show potential for delineating cancers on contrast-enhanced MRI (ce-MRI) but there are clinical scenarios in which administration of contrast is not desirable. We investigated performance of the CNN for d...
Machine learning has greatly facilitated the analysis of medical data, while the internal operations usually remain intransparent. To better comprehend these opaque procedures, a convolutional neural network for optical coherence tomography image seg...
IEEE journal of biomedical and health informatics
Feb 5, 2021
The quantity of leukocytes in papillary thyroid carcinoma (PTC) potentially have prognostic and treatment predictive value. Here, we propose a novel method for training a convolutional neural network (CNN) algorithm for segmenting leukocytes in PTCs....
Risk assessment of in-hospital mortality of patients at the time of hospitalization is necessary for determining the scale of required medical resources for the patient depending on the patient's severity. Because recent machine learning application ...
PURPOSE: To improve the signal-to-noise ratio (SNR) and image sharpness for whole brain isotropic 0.5 mm three-dimensional (3D) T weighted (Tw) turbo spin echo (TSE) intracranial vessel wall imaging (IVWI) at 3 T.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.