PURPOSE: This study investigated whether a deep-learning neural network can detect and segment surgical instrumentation and relevant tissue boundaries and landmarks within the retina using imaging acquired from a surgical microscope in real time, wit...
OBJECTIVE: To identify trends in complications following robot-assisted radical cystectomy (RARC) using a multi-institutional database, the International Robotic Cystectomy Consortium (IRCC).
Computational and mathematical methods in medicine
Oct 12, 2022
It is of great significance to explore the characteristic factors of postoperative nursing safety events in patients with otolaryngology surgery and to understand the characteristics of postoperative nursing safety events in otolaryngology surgery pa...
Journal of magnetic resonance imaging : JMRI
Oct 11, 2022
BACKGROUND: Previous studies have explored the potential on radiomics features of primary breast cancer tumor to identify axillary lymph node (ALN) metastasis. However, the value of deep learning (DL) to identify ALN metastasis remains unclear.
Convolutional neural networks (CNNs) have shown promise in discriminating between invasive and in situ melanomas. The aim of this study was to analyse how a CNN model, integrating both clinical close-up and dermoscopic images, performed compared with...
PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by i...
OBJECTIVES: To evaluate deep neural networks for automatic rib fracture detection on thoracic CT scans and to compare its performance with that of attending-level radiologists using a large amount of datasets from multiple medical institutions.
BACKGROUNDS AND OBJECTIVE: Evaluating the tympanic membrane (TM) using an otoendoscope is the first and most important step in various clinical fields. Unfortunately, most lesions of TM have more than one diagnostic name. Therefore, we built a databa...
OBJECTIVE: To investigate the effectiveness and safety of robot-assisted artificial urinary sphincter (AUS) implantation surgery for female patients with severe stress urinary incontinences (SUI) by performing a systematic literature review.
Journal of applied clinical medical physics
Oct 9, 2022
OBJECTIVES: To investigate the clinical utility of deep learning image reconstruction (DLIR) for improving image quality in low-dose chest CT in comparison with 40% adaptive statistical iterative reconstruction-Veo (ASiR-V40%) algorithm.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.