AIMC Topic: Retrospective Studies

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Learning curve of robot-assisted choledochal cyst excision in pediatrics: report of 60 cases.

Surgical endoscopy
BACKGROUND: Little data are available to assess the learning curve for robot-assisted surgery on choledochal cysts. The aim of this current study is to investigate the characteristics of the learning curve for robot-assisted choledochal cyst excision...

Combined Denoising and Suppression of Transient Artifacts in Arterial Spin Labeling MRI Using Deep Learning.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Arterial spin labeling (ASL) is a useful tool for measuring cerebral blood flow (CBF). However, due to the low signal-to-noise ratio (SNR) of the technique, multiple repetitions are required, which results in prolonged scan times and incr...

Acute kidney injury and its impact on renal prognosis after robot-assisted laparoscopic radical prostatectomy.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: This study assessed the incidence and impact of acute kidney injury (AKI) on renal prognosis in patients who underwent robot-assisted laparoscopic radical prostatectomy (RARP).

Deep-Learning F-FDG Uptake Classification Enables Total Metabolic Tumor Volume Estimation in Diffuse Large B-Cell Lymphoma.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Total metabolic tumor volume (TMTV), calculated from F-FDG PET/CT baseline studies, is a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires the segmentation of all malignant foci throughout the body. No consensus cu...

Automated classification of cancer from fine needle aspiration cytological image use neural networks: A meta-analysis.

Diagnostic cytopathology
BACKGROUND: The role of retrospective analysis has been evolved greatly in cancer research. We undertook this meta-analysis to evaluate the diagnostic value of Neural networks (NNs) in Fine needle aspiration cytological (FNAC) image of cancer.

A deep learning risk prediction model for overall survival in patients with gastric cancer: A multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Risk prediction of overall survival (OS) is crucial for gastric cancer (GC) patients to assess the treatment programs and may guide personalized medicine. A novel deep learning (DL) model was proposed to predict the risk for O...