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Machine learning for the prediction of blood transfusion risk during or after mitral valve surgery: a multicenter retrospective cohort study.

Scientific reports
This study aimed to identify the optimal prediction method and key preoperative variables for red blood cell (RBC) transfusion risk in patients undergoing mitral valve surgery. We conducted a retrospective study involving 1477 patients from eight lar...

High transposable element expression in sarcomas is associated with increased immune infiltrates and improved outcomes including after immunotherapy.

Journal for immunotherapy of cancer
BACKGROUND: Response to immune checkpoint inhibition (ICI) in sarcomas is overall low and heterogeneous. Understanding determinants of ICI outcomes may improve efficacy and patient selection. Thus, we investigated whether the expression of transposab...

Predictive modelling of clinically significant depressive symptoms after coronary artery bypass graft surgery: protocol for a multicentre observational study in two Swiss hospitals (the PsyCor study).

BMJ open
INTRODUCTION: Coronary artery bypass grafting (CABG) remains one of the most commonly performed cardiac surgeries worldwide. Despite surgical advancements, a significant proportion of patients experience psychological distress following surgery, with...

Implementation of Fully Automated AI-Integrated System for Body Composition Assessment on Computed Tomography for Opportunistic Sarcopenia Screening: Multicenter Prospective Study.

JMIR formative research
BACKGROUND: Opportunistic computed tomography (CT) screening for the evaluation of sarcopenia and myosteatosis has been gaining emphasis. A fully automated artificial intelligence (AI)-integrated system for body composition assessment on CT scans is ...

Nurses' Intention to Integrate AI Into Their Practice: Survey Study in Canada.

JMIR nursing
BACKGROUND: The integration of artificial intelligence (AI) into health care is set to revolutionize the sector, offering opportunities to enhance diagnostic accuracy, personalize treatment, and improve patient outcomes. However, little is known abou...

Proposition of a new, minimally-invasive, software smartphone device to predict sleep apnea and its severity.

Sleep & breathing = Schlaf & Atmung
PURPOSE: obstructive sleep apnea is underdiagnosed due to limited access to polysomnography (PSG). We aimed to assess the performances of Apneal, an application recording sound and movements thanks to a smartphone's microphone, accelerometer and gyro...

Interpretable machine learning model predicts 1-year inguinal hernia risk after robot-assisted radical prostatectomy.

Journal of robotic surgery
Inguinal hernia represents a clinically significant yet underreported complication of robot-assisted radical prostatectomy (RARP) for localized prostate cancer, with a notably high incidence within the first postoperative year. Despite its adverse im...

EEG Connectivity is an Objective Signature of Reduced Consciousness and Sleep Depth.

Brain topography
Different levels of reduced consciousness characterise human sleep stages at the behavioural level. On electroencephalography (EEG), the identification of sleep stages predominantly relies on localised oscillatory power within distinct frequency band...

Progesterone for Traumatic Brain Injury, Experimental Clinical Treatment III Trial Revisited: Objective Classification of Traumatic Brain Injury With Brain Imaging Segmentation and Biomarker Levels.

Critical care explorations
OBJECTIVE: This post hoc study of the Progesterone for Traumatic Brain Injury, Experimental Clinical Treatment (ProTECT) III trial investigates whether improving traumatic brain injury (TBI) classification, using serum biomarkers (glial fibrillary ac...

DeepGAM: An interpretable deep neural network using generalized additive model for depression diagnosis: Data from the heart and soul study.

PloS one
Deep neural networks have achieved significant performance breakthroughs across a range of tasks. For diagnosing depression, there has been increasing attention on estimating depression status from personal medical data. However, the neural networks ...