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The clinical impact of robot-assisted laparoscopic rectal cancer surgery associated with robot-assisted radical prostatectomy.

Asian journal of endoscopic surgery
INTRODUCTION: Robot-assisted laparoscopic surgery has been performed in various fields, especially in the pelvic cavity. However, little is known about the utility of robot-assisted laparoscopic rectal cancer surgery associated with robot-assisted ra...

Deep learning-based framework for the distinction of membranous nephropathy: a new approach through hyperspectral imagery.

BMC nephrology
BACKGROUND: Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic membranous nephropathy (IMN) and hepatitis B virus-related membranous nephropathy (HBV-MN). However, the morphologic differences are not visible ...

Multicenter Experience in Robot-Assisted Minimally Invasive Esophagectomy - a Comparison of Hybrid and Totally Robot-Assisted Techniques.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Oncological esophageal surgery has evolved significantly in the last decades. From open esophagectomy over (hybrid) minimally invasive surgery, nowadays, robot-assisted minimally invasive esophagectomy (RAMIE) approaches are applied. Curr...

Performance optimisation of deep learning models using majority voting algorithm for brain tumour classification.

Computers in biology and medicine
BACKGROUND: Although biopsy is the gold standard for tumour grading, being invasive, this procedure also proves fatal to the brain. Thus, non-invasive methods for brain tumour grading are urgently needed. Here, a magnetic resonance imaging (MRI)-base...

Prediction of venous thromboembolism with machine learning techniques in young-middle-aged inpatients.

Scientific reports
Accumulating studies appear to suggest that the risk factors for venous thromboembolism (VTE) among young-middle-aged inpatients are different from those among elderly people. Therefore, the current prediction models for VTE are not applicable to you...

Predicting malaria epidemics in Burkina Faso with machine learning.

PloS one
Accurately forecasting the case rate of malaria would enable key decision makers to intervene months before the onset of any outbreak, potentially saving lives. Until now, methods that forecast malaria have involved complicated numerical simulations ...

Diagnosis of central serous chorioretinopathy by deep learning analysis of en face images of choroidal vasculature: A pilot study.

PloS one
PURPOSE: To diagnose central serous chorioretinopathy (CSC) by deep learning (DL) analyses of en face images of the choroidal vasculature obtained by optical coherence tomography (OCT) and to analyze the regions of interest for the DL from heatmaps.

Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID).

Scientific reports
In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortality can significantly improve triage, bed allocation, timely management, and possibly, outcome. The study objective is to develop and validate individu...