AIMC Topic: Retrospective Studies

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Comparison of transvaginal mesh surgery and robot-assisted sacrocolpopexy for pelvic organ prolapse.

BMC surgery
BACKGROUND: Pelvic organ prolapse (POP) is greatly affecting the quality of life (QOL) of women. There are some surgical techniques for POP repair, for example, transvaginal mesh surgery (TVM), laparoscopic sacrocolpopexy (LSC), and robot-assisted sa...

Deep Learning-Based Intraoperative Stent Graft Segmentation on Completion Digital Subtraction Angiography During Endovascular Aneurysm Repair.

Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists
PURPOSE: Modern endovascular hybrid operating rooms generate large amounts of medical images during a procedure, which are currently mostly assessed by eye. In this paper, we present fully automatic segmentation of the stent graft on the completion d...

Cognitive Challenges Are Better in Distinguishing Binge From Nonbinge Drinkers: An Exploratory Deep-Learning Study of fMRI Data of Multiple Behavioral Tasks and Resting State.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Studies have identified imaging markers of binge drinking. Functional connectivity during both task challenges and resting state was shown to distinguish binge and nonbinge drinkers. However, no studies have compared the efficacy of task ...

Predicting the risk of dental implant loss using deep learning.

Journal of clinical periodontology
AIM: To investigate the feasibility of predicting dental implant loss risk with deep learning (DL) based on preoperative cone-beam computed tomography.

Robot-Assisted General Surgery Procedures at the Veterans Health Administration: A Comparison of Surgical Techniques.

The Journal of surgical research
INTRODUCTION: The use of the robot in general surgery has exploded in the last decade. The Veterans Health Administration presents a unique opportunity to study differences between surgical approaches due to the ability to control for health system a...

Performance of a generative adversarial network using ultrasound images to stage liver fibrosis and predict cirrhosis based on a deep-learning radiomics nomogram.

Clinical radiology
AIM: To investigate the performance of a generative adversarial network (GAN) model for staging liver fibrosis and its radiomics-based nomogram for predicting cirrhosis.

Utility of artificial intelligence with deep learning of hematoxylin and eosin-stained whole slide images to predict lymph node metastasis in T1 colorectal cancer using endoscopically resected specimens; prediction of lymph node metastasis in T1 colorectal cancer.

Journal of gastroenterology
BACKGROUND: When endoscopically resected specimens of early colorectal cancer (CRC) show high-risk features, surgery should be performed based on current guidelines because of the high-risk of lymph node metastasis (LNM). The aim of this study was to...

Combined Deep Learning-based Super-Resolution and Partial Fourier Reconstruction for Gradient Echo Sequences in Abdominal MRI at 3 Tesla: Shortening Breath-Hold Time and Improving Image Sharpness and Lesion Conspicuity.

Academic radiology
RATIONALE AND OBJECTIVES: To investigate the impact of a prototypical deep learning-based super-resolution reconstruction algorithm tailored to partial Fourier acquisitions on acquisition time and image quality for abdominal T1-weighted volume-interp...

Robot-assisted laparoscopy repair of uterine isthmocele: A two-center observational study.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To analyze outcomes and postoperative complications in patients undergoing robot-assisted isthmocele repair.