AIMC Topic: Retrospective Studies

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Retzius-sparing Robotic Radical Prostatectomy for Surgeons in the Learning Curve: A Propensity Score-matching Analysis.

European urology focus
BACKGROUND: Several authors claimed that the Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) needs a prolonged learning curve, and outcomes during this phase could be suboptimal.

Hierarchical Analysis of Factors Associated with T Staging of Gastric Cancer by Endoscopic Ultrasound.

Digestive diseases and sciences
BACKGROUND: Size, ulcer, differentiation, and location are known to be factors affecting the T stage accuracy of EUS in gastric cancer. However, whether an interaction exists among recognized variables is poorly understood. The aim of this study was ...

Deep Learning-Based Risk Model for Best Management of Closed Groin Incisions After Vascular Surgery.

The Journal of surgical research
BACKGROUND: Reduced surgical site infection (SSI) rates have been reported with use of closed incision negative pressure therapy (ciNPT) in high-risk patients.

Deep Learning for Automated Sorting of Retinal Photographs.

Ophthalmology. Retina
PURPOSE: Though the domain of big data and artificial intelligence in health care continues to evolve, there is a lack of systemic methods to improve data quality and streamline the preparation process. To address this, we aimed to develop an automat...

Impact of hybrid supervision approaches on the performance of artificial intelligence for the classification of chest radiographs.

Computers in biology and medicine
PURPOSE: To evaluate the impact of different supervision regimens on the training of artificial intelligence (AI) in the classification of chest radiographs as normal or abnormal in a moderately sized cohort of individuals more likely to be outpatien...

Computer-aided Detection of Brain Metastases in T1-weighted MRI for Stereotactic Radiosurgery Using Deep Learning Single-Shot Detectors.

Radiology
Background Brain metastases are manually identified during stereotactic radiosurgery (SRS) treatment planning, which is time consuming and potentially challenging. Purpose To develop and investigate deep learning (DL) methods for detecting brain meta...

Deep-Learning Detection of Cancer Metastases to the Brain on MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Approximately one-fourth of all cancer metastases are found in the brain. MRI is the primary technique for detection of brain metastasis, planning of radiotherapy, and the monitoring of treatment response. Progress in tumor treatment now ...