AIMC Topic: Retrospective Studies

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Application of artificial intelligence-based computer-assisted diagnosis on synthetic mammograms from breast tomosynthesis: comparison with digital mammograms.

European radiology
OBJECTIVE: To compare the diagnostic agreement and performances of synthetic and conventional mammograms when artificial intelligence-based computer-assisted diagnosis (AI-CAD) is applied.

Robot-Assisted Cystectomy and Ileal Conduit for Neurogenic Bladder: Comparison of Extracorporeal Intracorporeal Urinary Diversion.

Journal of endourology
The aim of the present study was to compare the perioperative outcomes of extracorporeal (EXTRA) intracorporeal (INTRA) urinary diversion in patients undergoing robotic cystectomy and ileal conduit for neurogenic bladder. All consecutive patients ...

Performance of Deep Learning and Genitourinary Radiologists in Detection of Prostate Cancer Using 3-T Multiparametric Magnetic Resonance Imaging.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Several deep learning-based techniques have been developed for prostate cancer (PCa) detection using multiparametric magnetic resonance imaging (mpMRI), but few of them have been rigorously evaluated relative to radiologists' performance ...

Development and validation of a clinically applicable deep learning strategy (HONORS) for pulmonary nodule classification at CT: A retrospective multicentre study.

Lung cancer (Amsterdam, Netherlands)
PURPOSE: To propose a practical strategy for the clinical application of deep learning algorithm, i.e., Hierarchical-Ordered Network-ORiented Strategy (HONORS), and a new approach to pulmonary nodule classification in various clinical scenarios, i.e....

An imageomics and multi-network based deep learning model for risk assessment of liver transplantation for hepatocellular cancer.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
INTRODUCTION: Liver transplantation (LT) is an effective treatment for hepatocellular carcinoma (HCC), the most common type of primary liver cancer. Patients with small HCC (<5 cm) are given priority over others for transplantation due to clinical al...

Meniscal lesion detection and characterization in adult knee MRI: A deep learning model approach with external validation.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Evaluation of a deep learning approach for the detection of meniscal tears and their characterization (presence/absence of migrated meniscal fragment).

Convolutional neural network for classifying primary liver cancer based on triple-phase CT and tumor marker information: a pilot study.

Japanese journal of radiology
PURPOSE: To develop convolutional neural network (CNN) models for differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) and predicting histopathological grade of HCC.

A machine learning approach to personalized dose adjustment of lamotrigine using noninvasive clinical parameters.

Scientific reports
The pharmacokinetic variability of lamotrigine (LTG) plays a significant role in its dosing requirements. Our goal here was to use noninvasive clinical parameters to predict the dose-adjusted concentrations (C/D ratio) of LTG based on machine learnin...