AIMC Topic: Retrospective Studies

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Short-term outcomes of robot-assisted versus conventional laparoscopic surgery for early-stage endometrial cancer: A retrospective, single-center study.

The journal of obstetrics and gynaecology research
AIM: We compared the short-term outcomes between conventional laparoscopic surgery (CLS) and robot-assisted surgery (RAS) to assess the technical feasibility of the latter for early-stage endometrial cancer.

A machine learning approach to risk assessment for alcohol withdrawal syndrome.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
At present, risk assessment for alcohol withdrawal syndrome relies on clinical judgment. Our aim was to develop accurate machine learning tools to predict alcohol withdrawal outcomes at the individual subject level using information easily attainable...

Utilization of a Peritoneal Interposition Flap to Prevent Symptomatic Lymphoceles After Robotic Radical Prostatectomy and Bilateral Pelvic Lymph Node Dissection.

Journal of endourology
The peritoneal interposition flap (PIF) has been shown to prevent postoperative symptomatic lymphocele (SL) formation after robot-assisted radical prostatectomy (RARP) and pelvic lymph node dissection (PLND). The PIF inhibits the mobilized bladder f...

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Sickle cell disease (SCD) is a genetic disorder of the red blood cells, resulting in multiple acute and chronic complications, including pain episodes, stroke, and kidney disease. Patients with SCD develop chronic organ dysfunction, which...

RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy Via Deep Learning.

International journal of radiation oncology, biology, physics
PURPOSE: Detailed and accurate absorbed dose calculations from radiation interactions with the human body can be obtained with the Monte Carlo (MC) method. However, the MC method can be slow for use in the time-sensitive clinical workflow. The aim of...

Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers' performance.

Japanese journal of radiology
PURPOSE: To evaluate the usefulness of deep learning-assisted diagnosis for identifying hyperdense middle cerebral artery sign (HMCAS) on non-contrast computed tomography in comparison with the diagnostic performance of neuroradiologists.

Deep learning based classification of solid lipid-poor contrast enhancing renal masses using contrast enhanced CT.

The British journal of radiology
OBJECTIVE: Establish a workflow that utilizes convolutional neural nets (CNN) to classify solid, lipid-poor, contrast enhancing renal masses using multiphase contrast enhanced CT (CECT) images and to assess the performance of the resulting network.

Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network.

Nature medicine
The electrocardiogram (ECG) is a widely used medical test, consisting of voltage versus time traces collected from surface recordings over the heart. Here we hypothesized that a deep neural network (DNN) can predict an important future clinical event...

CT-based radiomic features to predict pathological response in rectal cancer: A retrospective cohort study.

Journal of medical imaging and radiation oncology
INTRODUCTION: Innovative biomarkers to predict treatment response in rectal cancer would be helpful in optimizing personalized treatment approaches. In this study, we aimed to develop and validate a CT-based radiomic imaging biomarker to predict path...

Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on I post-ablation whole-body planar scans.

Scientific reports
The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on I post-ablation whole-body planar scans (RxWBSs) is important in tracking the progression of the metastatic lymph nodes (mLNs) of patients with papillary thyroid cancer (...