Cardiovascular

Acute Coronary Syndrome

Latest AI and machine learning research in acute coronary syndrome for healthcare professionals.

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Showing 274-294 of 8,030 articles
High Sensitivity Cardiac Troponin I Detection via MP-Locked Aptamer and Multimeric DNAzyme-Coupled Hyperbranched Hybridization Chain Reaction.

Timely and sensitive detection of cardiac troponin I (cTnI) is critical for early diagnosis of myoca...

Feb 2026 41732038
First-line risk stratification with machine learning models facilitates rapid triage for non-ST-elevation myocardial infarction.

Timely diagnosis of non-ST-elevation myocardial infarction (NSTEMI) remains challenging, as current ...

(1)
Feb 2026 41729857
Multicentre development and validation of a risk model integrating immunotherapy and coagulation biomarkers for thrombosis in autoimmune neurological disorders.

PURPOSE: Patients with Autoimmune Neurological Disorders (ANDs) require routine immunomodulatory the...

(1)
Feb 2026 41723895
Neoadjuvant Radiation is Causally Linked to Increased Operative Time and Perioperative Blood Transfusion in Pancreatic Ductal Adenocarcinoma.

INTRODUCTION: Blood transfusion in patients undergoing surgical resection for pancreatic ductal aden...

Feb 2026 41719621
Platelets as immune sensors: monitoring immune dynamics and diagnosing disease states across multiple disorders.

BACKGROUND: Beyond their classical roles in haemostasis and thrombosis, platelets have been recognis...

(2)
Feb 2026 41719795
Explainable machine learning for risk prediction of acute cardiac tamponade during atrial fibrillation ablation.

Cardiac tamponade is a rare yet catastrophic complication during atrial fibrillation (AF) catheter a...

Feb 2026 41703170
Prediction model for deep vein thrombosis stability based on multiple machine learning methods.

BackgroundThis study aimed to develop multiple machine learning (ML) models to predict DVT stability...

(2)
Feb 2026 41697123
Toward an explainable AI-Based clinical decision support system for predicting adverse outcomes in Rhabdomyolysis.

Rhabdomyolysis is a severe condition with high morbidity and mortality, driven by complications like...

Feb 2026 41693049
Interpretable multimodal machine learning model for predicting health risks of patients with heart failure.

Heart failure (HF) is one of the major causes of morbidity and mortality globally, necessitating acc...

Feb 2026 41698516
A Machine Learning-Based Prognostic Model for Sepsis-Associated Liver Injury Using Routine Indicators.

OBJECTIVE: Sepsis-associated liver injury (SALI) occurs in approximately 40% of sepsis cases and is ...

Feb 2026 41689832
Explainable ML for ACS culprit plaques: a multidimensional CCTA model highlighting hemodynamic increment.

To develop an interpretable, multi-parameter machine learning (ML) model that integrates plaque morp...

Feb 2026 41686335
Toward practical screening of mortality risk: Insights from interpretable machine learning in NHANES.

BACKGROUND: Efficient community-based screening for individuals at high risk of mortality is a major...

Feb 2026 41809735
Deep Learning and Machine Learning for Differentiation Between Contrast Extravasation and Hemorrhagic Transformation in Post-Thrombectomy Stroke CT.

BACKGROUND: Mechanical thrombectomy (MT) improves outcomes in acute ischemic stroke (AIS) but often ...

(1)
Feb 2026 41687434
[Cardiology : what's new in 2025].

In 2025, significant progress has been made in the management of heart failure and cardiovascular di...

Feb 2026 41674255
Practical machine learning model for early and accurate prediction of disseminated intravascular coagulation before its progression to an overt stage.

BACKGROUND AND AIMS: In patients with sepsis, anticoagulant therapy is expected to have maximal effi...

(1)
Feb 2026 41667115
Coronary revascularization: a long-term perspective.

This paper will forecast advancements in coronary revascularization by 2040, drawing on historical t...

(1)
Feb 2026 41271218
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