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Cohort Studies

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Machine learning methods to predict attrition in a population-based cohort of very preterm infants.

Scientific reports
The timely identification of cohort participants at higher risk for attrition is important to earlier interventions and efficient use of research resources. Machine learning may have advantages over the conventional approaches to improve discriminati...

The role of preoperative prostatic shape in the recovery of urinary continence after robotic radical prostatectomy: a single cohort analysis.

Prostate cancer and prostatic diseases
BACKGROUND: To explore the role of preoperative MRI prostate shape in urinary incontinence after robot-assisted radical prostatectomy (RARP).

Local recurrence of robot-assisted total mesorectal excision: a multicentre cohort study evaluating the initial cases.

International journal of colorectal disease
PURPOSE: Evidence regarding local recurrence rates in the initial cases after implementation of robot-assisted total mesorectal excision is limited. This study aims to describe local recurrence rates in four large Dutch centres during their initial c...

Predicting persistent central serous chorioretinopathy using multiple optical coherence tomographic images by deep learning.

Scientific reports
We sought to predict whether central serous chorioretinopathy (CSC) will persist after 6 months using multiple optical coherence tomography (OCT) images by deep convolutional neural network (CNN). This was a multicenter, retrospective, cohort study. ...

The robotic-assisted extended "Sistrunk" approach for tumors of the upper aerodigestive tract with limited transoral access: First description of oncological and functional outcomes.

Head & neck
We report on the first clinical experience with the robotic-assisted extended "Sistrunk" approach (RESA) for access to constrained spaces of the upper aerodigestive tract. This prospective case cohort study include six patients that underwent RESA if...

Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study.

BMC neurology
BACKGROUNDS: We aimed to develop and validate machine learning (ML) models for 30-day stroke mortality for mortality risk stratification and as benchmarking models for quality improvement in stroke care.

Results of robotic TAPP and conventional laparoscopic TAPP in an outpatient setting: a cohort study in Switzerland.

Langenbeck's archives of surgery
PURPOSE: Recently, robotic surgery has been increasingly performed in hernia surgery. Although feasibility and safety of robot-assisted inguinal hernia repair in an inpatient setting have been already shown, its role in outpatient hernia surgery has ...

Machine Learning Models for the Diagnosis and Prognosis Prediction of High-Grade B-Cell Lymphoma.

Frontiers in immunology
High-grade B-cell lymphoma (HGBL) is a newly introduced category of rare and heterogeneous invasive B-cell lymphoma (BCL), which is diagnosed depending on fluorescence hybridization (FISH), an expensive and laborious analysis. In order to identify H...