Myocardial Infarction

Engineering the Interfacial Charge Transfer Dynamics by Plasmonic S-Scheme Heterojunctions for Machine-Learning-Assisted Dual-Mode Immunoassays.

The development of photoelectrochemical (PEC)-coupled dual-mode biosensors, combined with multivaria...

DPP-DTT Nanowire Phototransistors for Optoelectronic Synapses in EMG and ECG Signal Classification.

A neuromorphic phototransistor based on nanowire-patterned diketopyrrolo-pyrrole-dithienylthieno[3,2...

AI-enhanced recognition of occlusions in acute coronary syndrome (AERO-ACS): a retrospective study.

BACKGROUND: Artificial intelligence (AI) augmentation of ECG assessment has significant potential to...

Beyond the type 1 pattern: comprehensive risk stratification in Brugada syndrome.

Brugada Syndrome (BrS) is an inherited cardiac ion channelopathy associated with an elevated risk of...

Road damage detection based on improved YOLO algorithm.

With urbanization accelerating and transportation demand growing, road damage has become an increasi...

Prescreening depression using wearable electrocardiogram and photoplethysmogram data from a psycholinguistic experiment.

Depression is a prevalent mental health disorder that significantly impacts well-being and qual...

Thermodynamic analysis and intelligent modeling of statin drugs solubility in supercritical carbon dioxide.

Evaluating the solubility of various drugs in supercritical CO is a fundamental step in developing a...

Investigating the Impact of the Stationarity Hypothesis on Heart Failure Detection using Deep Convolutional Scattering Networks and Machine Learning.

Detection of Cardiovascular Diseases (CVDs) has become crucial nowadays, as the World Health Organiz...

Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation.

Atrial fibrillation (AF) increases the risk of adverse cardiovascular events, yet the underlying bio...

AI-Guided Decision Support in Acute Cardiac Care: From Chest Pain to STEMI.

Artificial intelligence (AI) is rapidly transforming the landscape of acute cardiac care, offering n...

Machine learning-based high-benefit approach versus traditional high-risk approach in statin therapy: the Shizuoka Kokuho database study.

Statins are widely prescribed for the primary prevention of cardiovascular diseases, yet individual ...

Failure of standard contemporary ST-elevation myocardial infarction electrocardiogram criteria to reliably identify acute occlusion of the left anterior descending coronary artery.

AIMS: ST-elevation (STE) criteria on the electrocardiogram (ECG) are poorly sensitive for acute coro...

Identifying key physiological and clinical factors for traumatic brain injury patient management using network analysis and machine learning.

In the intensive care unit (ICU), managing traumatic brain injury (TBI) patients presents significan...

The role of face regions in remote photoplethysmography for contactless heart rate monitoring.

Heart rate (HR) estimation is crucial for early cardiovascular diagnosis, continuous monitoring, and...

Artificial Intelligence-Enabled Short-Term Ambulatory Monitoring ECG during Sinus Rhythm for Prediction of Hidden Atrial Fibrillation.

BACKGROUND: Screening of asymptomatic/occult atrial fibrillation (AF) remains challenging. This stud...

Machine Learning Identification of Athlete Sport Type Through ECG Analysis.

Convolutional Neural Network Fused With Recurrent Network for ECG-Based Detection of Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic Cardiomyopathy (HCM) affects the left ventricle of the heart, leading to th...

Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients.

BACKGROUND: Coronary artery disease (CAD) remains a leading cause of global mortality, with stroke c...

Functionalized Nanofinger Enhances Pretrained Language Model Performance for Ultrafast Early Warning of Heart Attacks.

Heart attacks are the leading cause of death worldwide, which means an accurate early warning system...

Deep learning to identify stroke within 4.5 h using DWI and FLAIR in a prospective multicenter study.

To enhance thrombolysis eligibility in acute ischemic stroke, we developed a deep learning model to ...

ISENet: a deep learning model for detecting ischemic ST changes in long-term ECG monitoring.

Long-term ECG monitoring is crucial for detecting asymptomatic or intermittent myocardial ischemia, ...