Journal of neuroengineering and rehabilitation
Jul 3, 2021
BACKGROUND: Transfemoral amputation is a serious intervention that alters the locomotion pattern, leading to secondary disorders and reduced quality of life. The outcomes of current gait rehabilitation for TFAs seem to be highly dependent on factors ...
PURPOSE: To diagnose central serous chorioretinopathy (CSC) by deep learning (DL) analyses of en face images of the choroidal vasculature obtained by optical coherence tomography (OCT) and to analyze the regions of interest for the DL from heatmaps.
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.
BACKGROUND & AIMS: Barrett's epithelium measurement using widely accepted Prague C&M classification is highly operator dependent. We propose a novel methodology for measuring this risk score automatically. The method also enables quantification of th...
Simulation is increasingly being used to train surgeons and access technical competency in robotic skills. The construct validity of using simulation performance for high-stakes examinations such as credentialing has not been studied appropriately. T...
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
May 17, 2021
HL7 Fast Healthcare Interoperability Resources (FHIR) is one of the current data standards for enabling electronic healthcare information exchange. Previous studies have shown that FHIR is capable of modeling both structured and unstructured data fro...
The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the classic Prechtl general movements assessment (GMA)...
In the aging world population, the occurrence of neuromotor deficits arising from stroke and other medical conditions is expected to grow, demanding the design of new and more effective approaches to rehabilitation. In this paper, we show how the com...
Deep generative models, such as variational autoencoders (VAEs) or deep Boltzmann machines (DBMs), can generate an arbitrary number of synthetic observations after being trained on an initial set of samples. This has mainly been investigated for imag...
PURPOSE: Dual-source (DS) CT, dual-energy (DE) field of view (FoV) is limited to the size of the smaller detector array. The purpose was to establish a deep learning-based approach to DE extrapolation by estimating missing image data using data from ...