AIMC Topic: Retrospective Studies

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Deep learning-based classification of lower extremity arterial stenosis in computed tomography angiography.

European journal of radiology
PURPOSE: The purpose of this study is to develop and evaluate a deep learning model to assist radiologists in classifying lower extremity arteries based on the degree of arterial stenosis caused by plaque in lower extremity computed tomography angiog...

Development of artificial intelligence system for quality control of photo documentation in esophagogastroduodenoscopy.

Surgical endoscopy
BACKGROUND: Esophagogastroduodenoscopy (EGD) is generally a safe procedure, but adverse events often occur. This highlights the necessity of the quality control of EGD. Complete visualization and photo documentation of upper gastrointestinal (UGI) tr...

Predicting Glaucoma Development With Longitudinal Deep Learning Predictions From Fundus Photographs.

American journal of ophthalmology
PURPOSE: To assess whether longitudinal changes in a deep learning algorithm's predictions of retinal nerve fiber layer (RNFL) thickness based on fundus photographs can predict future development of glaucomatous visual field defects.

Prediction of Clinical Outcome in Patients with Large-Vessel Acute Ischemic Stroke: Performance of Machine Learning versus SPAN-100.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Traditional statistical models and pretreatment scoring systems have been used to predict the outcome for acute ischemic stroke patients (AIS). Our aim was to select the most relevant features in terms of outcome prediction on...

Short-term outcome after robot-assisted hiatal hernia and anti-reflux surgery-is there a benefit for the patient?

Langenbeck's archives of surgery
PURPOSE: The robotic system was introduced to overcome the technical limitations of conventional laparoscopy. For complex oncological operations, it appears to offer further advantages. With regard to hiatal hernia repair, its role has yet to be dete...

Deep learning-assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver.

European radiology
OBJECTIVES: To train a deep learning model to differentiate between pathologically proven hepatocellular carcinoma (HCC) and non-HCC lesions including lesions with atypical imaging features on MRI.

Long-Term Functional and Oncologic Outcomes of Robot-Assisted Partial Nephrectomy for Cystic Renal Tumors: A Single-Center Retrospective Study.

Journal of endourology
To evaluate the outcomes of robot-assisted partial nephrectomy (RAPN) in cystic renal tumors. We retrospectively analyzed patients who underwent RAPN for either cystic ( = 46) or solid ( = 271) renal tumors at Fujita Health University between 2010 ...

Perioperative and Functional Outcomes of Robot-Assisted Radical Prostatectomy in Octogenarian Men.

Journal of endourology
The functional and oncologic outcomes of robot-assisted radical prostatectomy (RARP) in octogenarians are not well studied. We sought to study the perioperative, functional, and oncologic outcomes of RARP in octogenarian men. Between January 2009 a...

Positive Surgical Margins After Robot-Assisted Partial Nephrectomy Predict Long-Term Oncologic Outcomes for Clinically Localized Renal Masses.

Journal of endourology
For patients with clinically localized renal masses, positive surgical margins (PSMs) after robotic partial nephrectomy (RPN) have been associated with a higher risk of disease recurrence, although some studies have challenged this conclusion. Owing...

Automated Lateral Ventricular and Cranial Vault Volume Measurements in 13,851 Patients Using Deep Learning Algorithms.

World neurosurgery
BACKGROUND: No large dataset-derived standard has been established for normal or pathologic human cerebral ventricular and cranial vault volumes. Automated volumetric measurements could be used to assist in diagnosis and follow-up of hydrocephalus or...