AIMC Topic: Retrospective Studies

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Magnetic Resonance Spectroscopy Spectral Registration Using Deep Learning.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning-based methods have been successfully applied to MRI image registration. However, there is a lack of deep learning-based registration methods for magnetic resonance spectroscopy (MRS) spectral registration (SR).

Propensity matched analysis of robotic and laparoscopic operations for mid-low rectal cancer: short-term comparison of anal function and oncological outcomes.

Journal of robotic surgery
Laparoscopic surgery for rectal cancer, while in some respects equivalent or even preferable to open surgery, is challenged in specific conditions where the tumor is located in the middle and lower third of the rectum. Robotic surgery equipped with a...

Cancer immunotherapy response prediction from multi-modal clinical and image data using semi-supervised deep learning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Immunotherapy is a standard treatment for many tumor types. However, only a small proportion of patients derive clinical benefit and reliable predictive biomarkers of immunotherapy response are lacking. Although deep learning ...

Deep-learning image reconstruction for 80-kVp pancreatic CT protocol: Comparison of image quality and pancreatic ductal adenocarcinoma visibility with hybrid-iterative reconstruction.

European journal of radiology
PURPOSE: To evaluate the image quality and visibility of pancreatic ductal adenocarcinoma (PDAC) in 80-kVp pancreatic CT protocol and compare them between hybrid-iterative reconstruction (IR) and deep-learning image reconstruction (DLIR) algorithms.

Survival outcomes of abdominal radical hysterectomy, laparoscopic radical hysterectomy, robot-assisted radical hysterectomy and vaginal radical hysterectomy approaches for early-stage cervical cancer: a retrospective study.

World journal of surgical oncology
BACKGROUND: This study compared the survival outcomes of abdominal radical hysterectomy (ARH) (N = 32), laparoscopic radical hysterectomy (LRH) (N = 61), robot-assisted radical hysterectomy (RRH) (N = 100) and vaginal radical hysterectomy (VRH) (N = ...

Analysis of ultrasonographic images using a deep learning-based model as ancillary diagnostic tool for diagnosing gallbladder polyps.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Accurately diagnosing gallbladder polyps (GBPs) is important to avoid misdiagnosis and overtreatment.

Robot-assisted radical cystectomy with intracorporeal urinary diversion: a Danish 11-year series.

BJU international
OBJECTIVES: To evaluate the oncological and perioperative outcomes from a large, single-centre, robot-assisted radical cystectomy (RARC) cohort performed with intracorporeal urinary diversion (ICUD).

Human examination and artificial intelligence in cephalometric landmark detection-is AI ready to take over?

Dento maxillo facial radiology
OBJECTIVES: To compare the precision of two cephalometric landmark identification methods, namely a computer-assisted human examination software and an artificial intelligence program, based on South African data.

Surgery of the alimentary tract for benign and malignant disease with the novel robotic platform HUGO RAS. A first world report of safety and feasibility.

The international journal of medical robotics + computer assisted surgery : MRCAS
INTRODUCTION: As robotic surgery increases its reach, novel platforms are being released. We present the first 17 consecutive cases of alimentary tract surgery performed with the Hugo RAS (Medtronic).

Development and Validation of a Machine Learning Model to Identify Patients Before Surgery at High Risk for Postoperative Adverse Events.

JAMA network open
IMPORTANCE: Identifying patients at high risk of adverse outcomes prior to surgery may allow for interventions associated with improved postoperative outcomes; however, few tools exist for automated prediction.