AIMC Topic: Retrospective Studies

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The PD-ROBOSCORE: A difficulty score for robotic pancreatoduodenectomy.

Surgery
BACKGROUND: Difficulty scoring systems are important for the safe, stepwise implementation of new procedures. We designed a retrospective observational study for building a difficulty score for robotic pancreatoduodenectomy.

Accuracies of various types of spinal robot in robot-assisted pedicle screw insertion: a Bayesian network meta-analysis.

Journal of orthopaedic surgery and research
BACKGROUND: With the popularization of robot-assisted spinal surgeries, it is still uncertain whether robots with different designs could lead to different results in the accuracy of pedicle screw placement. This study aimed to compare the pedicle sc...

Robot-assisted radical nephroureterectomy for upper tract urothelial carcinoma: Peri and postoperative outcomes.

Actas urologicas espanolas
INTRODUCTION: The treatment of urothelial tumours of the upper urinary tract at high risk of specific mortality is based on radical nephroureterectomy (RNU). Robotic-assisted laparoscopic radical nephroureterectomy (RARNU) is still under investigatio...

Automatic implant shape design for minimally invasive repair of pectus excavatum using deep learning and shape registration.

Computers in biology and medicine
Minimally invasive repair of pectus excavatum (MIRPE) is an effective method for correcting pectus excavatum (PE), a congenital chest wall deformity characterized by concave depression of the sternum. In MIRPE, a long, thin, curved stainless plate (i...

Precise acetabular positioning, discrepancy in leg length, and hip offset using a new seven-axis robot-assisted total hip arthroplasty system requires no learning curve: a retrospective study.

Journal of orthopaedic surgery and research
OBJECTIVE: The purpose of the present study was to determine the learning curve for a novel seven-axis robot-assisted total hip arthroplasty (RA-THA) system, and to explore whether it was able to provide greater accuracy in acetabular cup positioning...

A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study.

The Lancet. Digital health
BACKGROUND: Photographs of the external eye were recently shown to reveal signs of diabetic retinal disease and elevated glycated haemoglobin. This study aimed to test the hypothesis that external eye photographs contain information about additional ...

Deep learning-based recognition of key anatomical structures during robot-assisted minimally invasive esophagectomy.

Surgical endoscopy
OBJECTIVE: To develop a deep learning algorithm for anatomy recognition in thoracoscopic video frames from robot-assisted minimally invasive esophagectomy (RAMIE) procedures using deep learning.

Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study.

Cell reports. Medicine
Deep learning (DL) can predict microsatellite instability (MSI) from routine histopathology slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other biomarkers with high performance and whether DL predictions genera...

CT-based deep learning model for the prediction of DNA mismatch repair deficient colorectal cancer: a diagnostic study.

Journal of translational medicine
BACKGROUND: Stratification of DNA mismatch repair (MMR) status in patients with colorectal cancer (CRC) enables individual clinical treatment decision making. The present study aimed to develop and validate a deep learning (DL) model based on the pre...

Deep learning-based artificial intelligence model for classification of vertebral compression fractures: A multicenter diagnostic study.

Frontiers in endocrinology
OBJECTIVE: To develop and validate an artificial intelligence diagnostic system based on X-ray imaging data for diagnosing vertebral compression fractures (VCFs).