Myocardial Infarction

Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.

Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has better applicability to new patients. We compare ATE-estimation using randomized and observational ana...

Aggressive hydraTion in patients with ST-Elevation Myocardial infarction undergoing Primary percutaneous coronary intervention to prevenT contrast-induced nephropathy (ATTEMPT): Study design and protocol for the randomized, controlled trial, the ATTEMPT, RESCIND 1 (First study for REduction of contraSt-induCed nephropathy followINg carDiac catheterization) trial.

Adequate hydration is recommended for acute ST-elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention (PCI) to prevent contrast-induced nephropathy (CIN). However, the optimal hydration regimen has not been well established in these high-risk patients. The objective of this study is to evaluate the efficacy of a preprocedural loading dose plus postpr...

Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks.

GOAL: This paper presents a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system.

An Automatic Subject-Adaptable Heartbeat Classifier Based on Multiview Learning.

In this paper, a novel subject-adaptable heartbeat classification model is presented, in order to address the significant interperson variations in EC...

Medication Extraction from Electronic Clinical Notes in an Integrated Health System: A Study on Aspirin Use in Patients with Nonvalvular Atrial Fibrillation.

PURPOSE: The purpose of this study was to investigate whether aspirin use can be captured from the clinical notes in a nonvalvular atrial fibrillation...

Infraclavicular first rib resection for the treatment of acute venous thoracic outlet syndrome.

OBJECTIVE: Venous thoracic outlet syndrome (VTOS) is most commonly treated by transaxillary, supraclavicular, or paraclavicular approaches, based on s...

Automatic diagnosis of premature ventricular contraction based on Lyapunov exponents and LVQ neural network.

Premature ventricular contraction (PVC) is a common type of abnormal heartbeat. Without early diagnosis and proper treatment, PVC may result in seriou...

The impact of precise robotic lesion length measurement on stent length selection: ramifications for stent savings.

BACKGROUND/PURPOSE: Coronary stent deployment outcomes can be negatively impacted by inaccurate lesion measurement and inappropriate stent length sele...

ECG Prediction Based on Classification via Neural Networks and Linguistic Fuzzy Logic Forecaster.

The paper deals with ECG prediction based on neural networks classification of different types of time courses of ECG signals. The main objective is t...

Multimodal predictor of neurodevelopmental outcome in newborns with hypoxic-ischaemic encephalopathy.

Automated multimodal prediction of outcome in newborns with hypoxic-ischaemic encephalopathy is investigated in this work. Routine clinical measures a...

Comparison of model-based and expert-rule based electrocardiographic identification of the culprit artery in patients with acute coronary syndrome.

BACKGROUND AND PURPOSE: Culprit coronary artery assessment in the triage ECG of patients with suspected acute coronary syndrome (ACS) is relevant a pr...

A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG.

GOAL: This paper presents a methodology for the automatic detection of sleep apnea from single-lead ECG.

A Synergistic Role of Myeloperoxidase and High Sensitivity Troponin T in the Early Diagnosis of Acute Coronary Syndrome.

Aim of this study was to evaluate the role of Myeloperoxidase (MPO) and high sensitive Troponin T in the early diagnosis of acute coronary syndrome (A...

Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters.

Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue ...

Prevalence of aspirin resistance in Asian-Indian patients with stable coronary artery disease.

OBJECTIVE: To evaluate the prevalence of pharmacological resistance to aspirin therapy by measuring platelet functions using the technique of light tr...

ECG-based longitudinal risk prediction across diseases and organ systems

Artificial intelligence applied to routine electrocardiograms (ECGs) has largely focused on detecting existing disease or predicting individual cardio...

Evaluator-Dependent Patient-Adaptive ECG Lead-Channel Allocation

Patient-conditioned acquisition policies for ECG lead-channel selection can outperform population-wide fixed protocols by tailoring the channel budget...

Graph-Based Pseudo-multimodal Contrastive Learning for 12-Lead ECG Representations

12-lead electrocardiogram (ECG) is a standard, non-invasive examination widely used for diagnosing coronary artery disease, where clinical interpretat...

CardioFusion-AI: Robust ECG--PPG Fusion for Multimodal Physiological Monitoring Under Signal Degradation

Wearable electrocardiogram (ECG) and photoplethysmogram (PPG) sensors are complementary but individually fragile: motion artifact, poor contact, and s...

Test-Time Adaptation for ECG Classification via SQI-Gated Self-Training and Beat-Rhythm Consistency

Deep learning models for electrocardiogram (ECG) classification often suffer from significant performance degradation when deployed in unseen domains ...