AIMC Topic: Time Factors

Clear Filters Showing 1691 to 1700 of 2001 articles

Outcome of transoral robotic surgery for stage I-II oropharyngeal cancer.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Traditionally T1-2N0 oropharyngeal carcinoma is treated with a single treatment modality, being either radiotherapy or surgery. Currently, minimally invasive surgery, such as transoral robotic surgery (TORS), is gaining popularity. The aim of this st...

Heterogeneous cardiovascular effects of sodium-glucose cotransporter 2 inhibitors in type 2 diabetes: a causal forest and target trial emulation study.

European journal of preventive cardiology
AIMS: Evidence is limited as to who benefit the most from sodium-glucose cotransporter 2 inhibitors (SGLT2i), especially among people without elevated cardiovascular disease (CVD) risk. To address this knowledge gap, we investigated the heterogeneity...

Artificial intelligence-enhanced electrocardiogram diastolic function grade predicts post-septal myectomy mortality in hypertrophic cardiomyopathy.

The Journal of thoracic and cardiovascular surgery
BACKGROUNDS: Diastolic dysfunction is an important pathophysiologic feature of hypertrophic cardiomyopathy that is often challenging to determine noninvasively. This study investigated whether a novel artificial intelligence-enabled electrocardiograp...

Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study.

Computer assisted surgery (Abingdon, England)
This study evaluates the performance of deep learning models in the prediction of the end time of procedures performed in the cardiac catheterization laboratory (cath lab). We employed only the clinical phases derived from video analysis as input to ...

Machine learning using serial changes in proteinuria during initial steroid therapy to predict treatment response and immunosuppressant use in pediatric idiopathic nephrotic syndrome.

Clinical and experimental nephrology
BACKGROUND: Epidemiological studies on idiopathic nephrotic syndrome (INS) in children have identified no definitive factors predicting steroid-resistant nephrotic syndrome (SRNS) or frequent relapsing nephrotic syndrome. Research using machine learn...

A meta-learning method for estimation of causal excursion effects to assess time-varying moderation.

Biometrics
Advances in wearable technologies and health interventions delivered by smartphones have greatly increased the accessibility of mobile health (mHealth) interventions. Micro-randomized trials (MRTs) are designed to assess the effectiveness of the mHea...

Multifrequency Time-Dependent Deep Image Prior for Real-Time Free-Breathing Cardiac Imaging.

NMR in biomedicine
The aim of this study is to enable high temporal resolution functional cardiac imaging without breathholds or electrocardiogram (ECG) gating. Real-time MRI is essential for assessing heart function in patients with limited breathhold capacity or arrh...

`Probabilistic ensemble learning for prediction of stroke thrombectomy outcomes from the NeuroVascular Quality Initiative-Quality Outcomes Database (NVQI-QOD) Acute Ischemic Stroke Registry.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: Mechanical Thrombectomy (MT) is the standard of care in the interventional management of Acute Ischemic Stroke (AIS). The NVQI-QOD registry records detailed patient characteristics, pre-operative imaging, procedure metrics, and post-ope...