Cardiovascular

Self-supervised learning for label-free segmentation in cardiac ultrasound.

Segmentation and measurement of cardiac chambers from ultrasound is critical, but laborious and poor...

Harnessing an Artificial Intelligence-Based Large Language Model With Personal Health Record Capability for Personalized Information Support in Postsurgery Myocardial Infarction: Descriptive Qualitative Study.

BACKGROUND: Myocardial infarction (MI) remains a leading cause of morbidity and mortality worldwide....

Industrial-grade collaborative robots for motor rehabilitation after stroke and spinal cord injury: a systematic narrative review.

BACKGROUND: There is a growing interest in exploring industrial-grade collaborative robots (cobots) ...

Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.

Real time 2D phase contrast (RTPC) MRI is useful for flow quantification in atrial fibrillation (AF)...

Artificial intelligence-assisted left ventricular global longitudinal strain assessment in patients with acute myocardial infarction: a RESUS-AMI trial sub-analysis.

PURPOSE: The aim of this sub-analysis of the RESUS-AMI trial was to evaluate the correlation of arti...

Protein interactions, network pharmacology, and machine learning work together to predict genes linked to mitochondrial dysfunction in hypertrophic cardiomyopathy.

This study looked at possible targets for hypertrophic cardiomyopathy (HCM), a condition marked by t...

Identification and Validation of Glycosylation‑Related Genes in Ischemic Stroke Based on Bioinformatics and Machine Learning.

Ischemic stroke (IS) constitutes a severe neurological disorder with restricted treatment alternativ...

A deep-learning algorithm using real-time collected intraoperative vital sign signals for predicting acute kidney injury after major non-cardiac surgeries: A modelling study.

BACKGROUND: Postoperative acute kidney injury (PO-AKI) prediction models for non-cardiac major surge...

Flexor Synergy Assessment and Therapy for Persons With Stroke Using the ULIX Low Impedance Robot.

The flexor synergy after stroke results in involuntary activation of distal muscles when lifting the...

Challenges, optimization strategies, and future horizons of advanced deep learning approaches for brain lesion segmentation.

Brain lesion segmentation is challenging in medical image analysis, aiming to delineate lesion regio...

Risk for ocular hypertension progression to early glaucoma: A predictive model and key predictors.

BACKGROUND: Ocular hypertension (OHT) is the most significant risk factor for glaucoma. We aimed to ...

Retinal Ischemic Perivascular Lesions (RIPLs) as Potential Biomarkers for Systemic Vascular Diseases: A Narrative Review of the Literature.

Retinal ischemic perivascular lesions (RIPLs) are characteristic focal thinning of the inner nuclear...

Research on noninvasive electrophysiologic imaging based on cardiac electrophysiology simulation and deep learning methods for the inverse problem.

BACKGROUND: The risk stratification and prognosis of cardiac arrhythmia depend on the individual con...

Application and optimization of the U-Net++ model for cerebral artery segmentation based on computed tomographic angiography images.

Accurate segmentation of cerebral arteries on computed tomography angiography (CTA) images is essent...

Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis.

OBJECTIVE: In-hospital cardiac arrest (IHCA) presents a critical challenge with low survival rates a...

Fast and automatic coronary artery segmentation using nnU-Net for non-contrast enhanced magnetic resonance coronary angiography.

Non-contrast enhanced magnetic resonance coronary angiography (MRCA) is a promising coronary heart d...

A multi-site study of clinician perspectives in the lifecycle of an algorithmic risk prediction tool.

Recent advancements in the performative capacities of artificial intelligence (AI), machine learning...

Electrosurgical-laceration and stabilization of two PASCAL devices using artificial intelligence-based procedural planning: a case report.

BACKGROUND: Mitral transcatheter edge-to-edge repair (M-TEER) has been established as a treatment fo...

Development and external validation of a machine learning model for cardiac valve calcification early screening in dialysis patients: a multicenter study.

BACKGROUND: Cardiac valve calcification (CVC) is common in dialysis patients and associated with inc...

Artificial Intelligence to Evaluate Aortic Insufficiency: An Exercise in Machine Learning.

Unveiling fetal heart health: harnessing auto-metric graph neural networks and Hazelnut tree search for ECG-based arrhythmia detection.

Fetal electrocardiogram (ECG) provides a non-invasive means to assess fetal heart health, but isolat...