Myocardial Infarction

AI-based prediction of aspirin-exacerbated respiratory disease using nasal epithelial mRNA expression profiles.

BACKGROUND: Aspirin-exacerbated respiratory disease (AERD) is a distinct asthma endotype marked by asthma, nasal polyposis, and respiratory reactions to COX-1 inhibitors. Early and accurate identification of AERD remains clinically challenging. OBJECTIVE: We sought to develop and externally validate an artificial intelligence (AI)-based diagnostic model that uses nasal epithelial mRNA expression p...

Missing-data-aware machine learning prediction of in-hospital major adverse cardiovascular events after primary percutaneous coronary intervention for ST-segment elevation myocardial infarction.

Machine learning (ML) offers opportunities to improve prognostication after ST-segment elevation myocardial infarction (STEMI), but real-world registries frequently contain incomplete data, and inappropriate handling of missingness may degrade performance. We retrospectively evaluated 659 consecutive STEMI patients undergoing PCI during the index admission. The primary outcome was in-hospital majo...

AI-based Histologic Heterogeneity of Microvascular Obstruction at Cardiac MRI for Predicting MACEs: A Multicenter Study.

Background Microvascular obstruction (MVO) is strongly associated with adverse outcomes after ST-segment elevation myocardial infarction (STEMI). Howe...

Characterizing Central-Autonomic Dynamics During an Episodic Memory Task Using Multi-Modal Neural and Cardiomechanical Signals.

OBJECTIVE: Memory function underlies mental and behavioral health. While the role of the central nervous system (CNS) during episodic memory encoding ...

Cardiovascular Disease Classification System With ECG-Gating PCG Algorithm and Programmable AI Accelerator Design.

Cardiovascular diseases (CVDs) are among the leading causes of mortality. Traditional diagnostic methods require hospital visits and professional medi...

BioGAP-Ultra: A Modular Edge-AI Platform for Wearable Multimodal Biosignal Acquisition and Processing.

The growing demand for continuous physiological monitoring and human-machine interaction in real-world settings calls for wearable platforms that are ...

Long-term continuous monitoring of wearable ECG signals for atrial fibrillation detection.

Atrial Fibrillation (AFib) is the most common sustained cardiac arrhythmia and is associated with substantial morbidity and mortality, including incre...

Ultrasound-Mediated Thrombolysis: From Mechanistic Insights to Advanced Nanoplatforms and Clinical Translation.

Although pharmacological thrombolysis and mechanical thrombectomy are standard treatments for thromboembolic diseases, they are limited by hemorrhagic...

Synchrotron-Based Deep Learning Network of the Inner Ear: Development and Expert Validation.

OBJECTIVE: To develop and externally validate a deep learning segmentation network capable of automatically segmenting the inner ear in preoperative c...

Generalisable artificial intelligence ECG trained on public data for outcome prediction after transcatheter aortic valve replacement.

BACKGROUND: Artificial intelligence ECG (AI-ECG) models can predict cardiovascular outcomes, but their clinical adoption is limited by restricted acce...

Machine Learning-Based Periprocedural Prediction Model for No-Reflow Risk After Percutaneous Coronary Intervention in Patients With Acute Coronary Syndrome.

Coronary no-reflow (NR) after percutaneous coronary intervention (PCI) predicts adverse prognosis in patients with acute coronary syndrome (ACS). This...

Fully Biobased, Robust, and High-Conductivity Hydrogel for High-Fidelity Electrophysiological Monitoring and Deep Learning-Assisted Stroke Rehabilitation.

Developing sustainable bioelectronics that simultaneously integrate mechanical robustness, high conductivity, biocompatibility, and system-level funct...

An enhanced hypergraph CNN with adaptive focal loss for automated ECG heartbeat classification.

Deep learning techniques have shown significant promise for the automated diagnosis of CVD using ECG analysis. Nevertheless, several critical challeng...

Comparison of systolic and diastolic CT-FFR for myocardial ischemia diagnosis.

BACKGROUND: CT-derived fractional flow reserve (CT-FFR) is a powerful tool for identifying hemodynamic ischemia. Coronary CT angiography (CCTA) images...

Predicting immune checkpoint inhibitor cardiotoxicity using machine learning: a systematic review of model performance and methodological quality.

BACKGROUND: Immune checkpoint inhibitors (ICIs) significantly improve cancer outcomes but can cause rare, potentially fatal cardiotoxicity, including ...

A multi-branch vision transformer with GA-optimized focal loss for ECG signal classification.

Background The classification of electrocardiogram (ECG) signals is a critical task in detecting cardiac arrhythmias. However, challenges such as clas...

Survival prediction modeling for 1-year mortality in patients with ST elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI).

BACKGROUND: ST elevation myocardial infarction (STEMI) is a life-threatening condition, and is associated with significant mortality, especially in pa...

Prediction of Neurological Outcome and Mortality in Cardiac Arrest Patients: An Explainable Machine Learning Study Integrating HRV, EEG, and Clinical Features.

OBJECTIVE: Early and accurate prediction of neurological outcomes and mortality in comatose patients after cardiac arrest remains challenging. Multimo...

CODE-II: a large-scale dataset for artificial intelligence in ECG analysis.

Data-driven methods for electrocardiogram (ECG) interpretation are rapidly progressing. Large datasets have enabled advances in artificial intelligenc...

Multimodal digital phenotyping of bipolar disorder subtypes: Differences between bipolar disorder I and II based on passive and active behavioral features from smartphones.

BACKGROUND: Distinguishing between bipolar disorder type I and II constitutes a significant clinical challenge that relies on retrospective patient re...