Journal of minimally invasive gynecology
Jun 15, 2021
STUDY OBJECTIVE: To describe the surgical techniques and short-term outcomes for 33 cases of robot-assisted transvaginal natural orifice transluminal endoscopic surgery (RvNOTES) to treat endometriosis.
Journal of minimally invasive gynecology
Jun 15, 2021
STUDY OBJECTIVE: Obesity is a growing worldwide epidemic, and patients classified as obese undergoing gynecologic robotic surgery are at increased risk for surgical complications. This study aimed to evaluate the feasibility and outcomes of a surgica...
Annals of oncology : official journal of the European Society for Medical Oncology
Jun 15, 2021
BACKGROUND: Clinical management of soft tissue sarcoma (STS) is particularly challenging. Here, we used digital pathology and deep learning (DL) for diagnosis and prognosis prediction of STS.
There is little evidence on the applicability of deep learning (DL) in the segmentation of acute ischemic lesions on diffusion-weighted imaging (DWI) between magnetic resonance imaging (MRI) scanners of different manufacturers. We retrospectively inc...
OBJECTIVE: To assess the diagnostic performance and reader confidence in determining the resectability of pancreatic cancer at computed tomography (CT) using a new deep learning image reconstruction (DLIR) algorithm.
AJNR. American journal of neuroradiology
Jun 11, 2021
BACKGROUND AND PURPOSE: Artificial intelligence decision support systems are a rapidly growing class of tools to help manage ever-increasing imaging volumes. The aim of this study was to evaluate the performance of an artificial intelligence decision...
OBJECTIVE: This study evaluated the clinical utility of a phantom-based convolutional neural network noise reduction framework for whole-body-low-dose CT skeletal surveys.
Technical advancements significantly improve earlier diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various factors. We develop an artificial intelligence assistive diagnostic solution, AIATBS, to improve cervical liqu...
We aimed to create and validate a natural language processing algorithm to extract wound infection-related information from nursing notes. We also estimated wound infection prevalence in homecare settings and described related patient characteristics...
OBJECTIVE: This study evaluates the ability of several machine learning (ML) algorithms, developed using volumetric and texture data extracted from baseline F-FDG PET/CT studies performed initial staging of patient with esophageal cancer (EC), to pre...
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