Writing notes is the most widespread method to report clinical events. Therefore, most of the information about the disease history of a patient remains locked behind free-form text. Natural language processing (NLP) provides a solution to automatica...
PURPOSE: The Fundus photography vs Ophthalmoscopy Trial Outcomes in the Emergency Department (FOTO-ED) studies showed that ED providers poorly recognized funduscopic findings in patients in the ED. We tested a modified version of the Brain and Optic ...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Nov 4, 2023
PURPOSE: There is increasing interest in novel prognostic tools and predictive biomarkers to help identify, with more certainty, cerebral cavernous malformations (CCM) susceptible of bleeding if left untreated. We developed explainable quantitative-b...
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Nov 4, 2023
PURPOSE: The purpose of this study was to develop a model for predicting chemoradiation response in non-small cell lung cancer (NSCLC) patients by integrating radiomics and deep-learning features and combined intra- and peritumoral regions with pre-t...
Overcrowding of emergency departments is a global concern, leading to numerous negative consequences. This study aimed to develop a useful and inexpensive tool derived from electronic medical records that supports clinical decision-making and can be ...
Lesion scores on procurement donor biopsies are commonly used to guide organ utilization for deceased-donor kidneys. However, frozen sections present challenges for histological scoring, leading to inter- and intra-observer variability and inappropri...
The surgical management of rectal cancer is shifting toward more widespread use of robotics across a spectrum of medical centers. There is evidence that the oncologic outcomes are equivalent to laparoscopic resections, and the post-operative outcomes...
OBJECTIVE: Radiomic and deep learning studies based on magnetic resonance imaging (MRI) of liver tumor are gradually increasing. Manual segmentation of normal hepatic tissue and tumor exhibits limitations.
This study aimed to develop a deep learning (DL) algorithm for automated detection and localization of posterior ligamentous complex (PLC) injury in patients with acute thoracolumbar (TL) fracture on magnetic resonance imaging (MRI) and evaluate its ...
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