AIMC Topic: Prospective Studies

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Automated Magnetic Resonance Image Segmentation of Spinal Structures at the L4-5 Level with Deep Learning: 3D Reconstruction of Lumbar Intervertebral Foramen.

Orthopaedic surgery
OBJECTIVE: 3D reconstruction of lumbar intervertebral foramen (LIVF) has been beneficial in evaluating surgical trajectory. Still, the current methods of reconstructing the 3D LIVF model are mainly based on manual segmentation, which is laborious and...

Indocyanine green fluorescence in robot-assisted minimally invasive esophagectomy with intrathoracic anastomosis: a prospective study.

Updates in surgery
Indocyanine green fluorescence angiography (ICG-FA) allows for real-time intraoperative assessment of the perfusion of the gastric conduit during esophagectomy. The aim of this study was to investigate the effect of the implementation of ICG-FA durin...

Evaluation of Spatial Attentive Deep Learning for Automatic Placental Segmentation on Longitudinal MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Automated segmentation of the placenta by MRI in early pregnancy may help predict normal and aberrant placenta function, which could improve the efficiency of placental assessment and the prediction of pregnancy outcomes. An automated seg...

A Deep Learning Model for Automated Segmentation of Geographic Atrophy Imaged Using Swept-Source OCT.

Ophthalmology. Retina
PURPOSE: To present a deep learning algorithm for segmentation of geographic atrophy (GA) using en face swept-source OCT (SS-OCT) images that is accurate and reproducible for the assessment of GA growth over time.

A cumulative sum (CUSUM) analysis studying operative times and complications for a surgeon transitioning from laparoscopic to robot-assisted pediatric pyeloplasty: Defining proficiency and competency.

Journal of pediatric urology
INTRODUCTION: The transition from laparoscopic to robot-assisted procedures leads to potential increase in operative times and health care costs. Cumulative sum (CUSUM) analysis can objectively study the learning curve to detect significant changes i...

Machine learning applications in upper gastrointestinal cancer surgery: a systematic review.

Surgical endoscopy
BACKGROUND: Machine learning (ML) has seen an increase in application, and is an important element of a digital evolution. The role of ML within upper gastrointestinal surgery for malignancies has not been evaluated properly in the literature. Theref...

Coronary Artery Stent Evaluation by CTA: Impact of Deep Learning Reconstruction and Subtraction Technique.

AJR. American journal of roentgenology
Coronary CTA with hybrid iterative reconstruction (HIR) is prone to false-positive results for in-stent restenosis due to stent-related blooming artifact. The purpose of this study is to assess the impact of deep learning reconstruction (DLR), subt...

Long-term oncologic outcomes of robot-assisted versus open radical prostatectomy for prostate cancer with seminal vesicle invasion: a multi-institutional study with a minimum 5-year follow-up.

Journal of cancer research and clinical oncology
PURPOSE: This study aimed to compare the long-term oncological outcomes of robot-assisted radical prostatectomy (RARP) vs. open radical prostatectomy (ORP) in pathologically proven prostate cancer with seminal vesicle invasion (SVI).

Development and validation of a predictive model for peripherally inserted central catheter-related thrombosis in breast cancer patients based on artificial neural network: A prospective cohort study.

International journal of nursing studies
BACKGROUND: Peripherally inserted central catheters have been extensively applied in clinical practices. However, they are associated with an increased risk of thrombosis. To improve patient care, it is critical to timely identify patients at risk of...