BACKGROUND: Pediatric fractures are challenging to identify given the different response of the pediatric skeleton to injury compared to adults, and most artificial intelligence (AI) fracture detection work has focused on adults.
INTRODUCTION: Urinary dysfunctions are common sequelae following prostatectomy. This study aimed to discover factors that can predict urinary continence recovery at various time periods after robot-assisted laparoscopic radical prostatectomy (RARP).
Medical & biological engineering & computing
Sep 22, 2023
Deep convolutional neural networks (DCNNs) have demonstrated promising performance in classifying breast lesions in 2D ultrasound (US) images. Exiting approaches typically use pre-trained models based on architectures designed for natural images with...
The use of robotic-assisted surgery (RAS) in total knee arthroplasty (TKA) is becoming increasingly popular due to better precision, potentially superior outcomes and the ability to achieve alternative alignment strategies. The most commonly used ali...
INTRODUCTION: A steadily rising opioid pandemic has left the US suffering significant social, economic, and health crises. Machine learning (ML) domains have been utilized to predict prolonged postoperative opioid (PPO) use. This systematic review ai...
To compare the effectiveness of the Da Vinci Surgical Robot System (DSRS) "3 + 1" and "4 + 1" models for colorectal cancer (CRC). A total of 107 patients with CRC admitted to our hospital from February 2021 to May 2022 were selected for the retrospec...
OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathological regional nodal metastasis (pN+) in resectable lung adenocarcinoma varies, and their use across different generations of PET machines has not been t...
PURPOSE: MR arthrography (MRA) is the most accurate method for preoperatively diagnosing superior labrum anterior-posterior (SLAP) lesions, but diagnostic results can vary considerably due to factors such as experience. In this study, deep learning w...
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