AIMC Topic: Retrospective Studies

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Artificial intelligence to identify fractures on pediatric and young adult upper extremity radiographs.

Pediatric radiology
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.

Variations in predictors for urinary continence recovery at different time periods following robot-assisted radical prostatectomy.

Asian journal of endoscopic surgery
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).

Classification of breast lesions in ultrasound images using deep convolutional neural networks: transfer learning versus automatic architecture design.

Medical & biological engineering & computing
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...

Is Urethral Catheterization Necessary in Retzius-sparing Robot-assisted Radical Prostatectomy?

Urology
OBJECTIVE: To analyze whether urethral catheter (UC)-free anastomosis during Retzius-sparing radical prostatectomy (RP) results in worsening immediate perioperative and postoperative complications.

No Benefit of Robotic-Assisted over Computer-Assisted Surgery for Achieving Neutral Coronal Alignment in Total Knee Arthroplasty.

The journal of knee surgery
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...

Machine Learning Algorithms Predict Long-Term Postoperative Opioid Misuse: A Systematic Review.

The American surgeon
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...

Comparison of effectiveness and safety of Da Vinci robot's "3 + 1" and "4 + 1" modes of treatment for colorectal cancer.

Journal of robotic surgery
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...

A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.

Nuclear medicine communications
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...

Autologous Transplantation Tooth Guide Design Based on Deep Learning.

Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
BACKGROUND: Autologous tooth transplantation requires precise surgical guide design, involving manual tracing of donor tooth contours based on patient cone-beam computed tomography (CBCT) scans. While manual corrections are time-consuming and prone t...

Preliminary exploration of deep learning-assisted recognition of superior labrum anterior and posterior lesions in shoulder MR arthrography.

International orthopaedics
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...