AIMC Topic: Retrospective Studies

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Real-World Performance of Large Vessel Occlusion Artificial Intelligence-Based Computer-Aided Triage and Notification Algorithms-What the Stroke Team Needs to Know.

Journal of the American College of Radiology : JACR
PURPOSE: To evaluate the real-world performance of two FDA-approved artificial intelligence (AI)-based computer-aided triage and notification (CADt) detection devices and compare them with the manufacturer-reported performance testing in the instruct...

Diagnostic performance of deep learning-based reconstruction algorithm in 3D MR neurography.

Skeletal radiology
OBJECTIVE: The study aims to evaluate the diagnostic performance of deep learning-based reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and lumbosacral plexus.

Effect of artificial intelligence-based computer-aided diagnosis on the screening outcomes of digital mammography: a matched cohort study.

European radiology
OBJECTIVE: To investigate whether artificial intelligence-based computer-aided diagnosis (AI-CAD) can improve radiologists' performance when used to support radiologists' interpretation of digital mammography (DM) in breast cancer screening.

Outcomes of robot-assisted versus laparoscopic surgery for colorectal cancer in morbidly obese patients: A propensity score-matched analysis of the US Nationwide Inpatient Sample.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Morbid obesity is associated with poorer postoperative outcomes in colorectal cancer (CRC) patients. We aimed to evaluate short-term outcomes after robotic versus conventional laparoscopic CRC resection in morbidly obese patients.

Robot-assisted stereoencephalography vs subdural electrodes in the evaluation of temporal lobe epilepsy.

Epilepsia open
OBJECTIVE: Invasive video-electroencephalography (iVEEG) is the gold standard for evaluation of refractory temporal lobe epilepsy before second stage resective surgery (SSRS). Traditionally, the presumed seizure onset zone (SOZ) has been covered with...

A Deep Learning Pipeline Using Prior Knowledge for Automatic Evaluation of Placenta Accreta Spectrum Disorders With MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The diagnosis of prenatal placenta accreta spectrum (PAS) with magnetic resonance imaging (MRI) is highly dependent on radiologists' experience. A deep learning (DL) method using the prior knowledge that PAS-related signs are generally fo...

Deep learning-based reconstruction and 3D hybrid profile order technique for MRCP at 3T: evaluation of image quality and acquisition time.

European radiology
OBJECTIVES: To evaluate the image quality of the 3D hybrid profile order technique and deep-learning-based reconstruction (DLR) for 3D magnetic resonance cholangiopancreatography (MRCP) within a single breath-hold (BH) at 3 T magnetic resonance imagi...