Acute Coronary Syndrome

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). However, manual quantification of MVO is time-consuming and fails to capture the heterogeneity of microvascular injury. Purpose To evaluate an artificial intelligence (AI)-based model including automated MVO segmentation and radiomic feature extraction t...

Designing the Future of Hemostasis.

Bleeding disorders arising from dysfunctional platelet-protein interactions pose a significant clinical challenge due to their heterogeneity and complexity. Primary hemostasis is mediated by von Willebrand factor (VWF) and platelet surface receptors GPIbα and αIIbβ3. This protein triad is central to clot formation and interfering with their associated activity can cause several primary hemostasis ...

Machine learning prediction of PICC-associated thrombotic complications in critically ill patients.

BACKGROUND: Peripherally inserted central catheters (PICCs) are widely used vascular access devices in intensive care, yet thrombotic complications re...

A Multidimensional Integrated Strategy for Identifying Anti-thrombotic Quality Markers(Q-Markers) in Taohong Siwu Decoction through Combined Analysis of Chemical Profiling, Bioactivity, and Pharmacodynamic Efficacy.

ETHNOPHARMACOLOGICAL RELEVANCE: Taohong Siwu Decoction (TSD), originating from the Qing Dynasty medical text Gynecology Ice Mirror, is a representativ...

Predictors of warfarin therapeutic dose in cancer patients: a preliminary comparative study using machine learning-integrated explainable artificial intelligence and Bayesian models.

BACKGROUND: Warfarin dosing in cancer patients is challenging due to altered pathophysiology and variable responses. While machine learning offers pre...

Latent biochemical phenotypes delineate divergent health trajectories in older adults.

Ageing heterogeneity hampers prevention and care. We used routine biochemical panels and unsupervised learning to identify latent phenotypes in commun...

Machine learning based approaches for structure activity relationship analysis of heparanase inhibitors.

Human Heparanase (HPSE), the only mammalian endo-β-D-glucuronidase, plays an important role in extracellular matrix remodeling and the release of hepa...

Idiopathic Intracranial Hypertension Is Characterized by a Distinct Proteomic Profile.

OBJECTIVES: The pathophysiology of idiopathic intracranial hypertension (IIH) is poorly understood and disease-specific biomarkers are lacking. We aim...

Impact of Unfractionated Heparin Use on Maternal Bone Mineral Density During Pregnancy: A Retrospective Study Using AI-Assisted Radiographic Analysis.

PURPOSE: This study aimed to evaluate the impact of unfractionated heparin (UFH) use during pregnancy on maternal bone mineral density (BMD) by assess...

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...

Prediction of cancer-associated thrombosis by machine learning: results from the Vienna Cancer and Thrombosis Study.

BACKGROUND: Improved risk prediction of cancer-associated venous thromboembolism (VTE) remains an unmet clinical need. We aimed to apply machine learn...

Personalised thrombo-embolic risk prediction after endometrial cancer surgery: an explainable AI approach using SHAP.

To address the clinical challenge of postoperative lower extremity deep vein thrombosis (LEDVT) in endometrial cancer care, this study establishes an ...

Stress hyperglycemia ratio improves 28-day mortality prediction beyond GRACE score in critically ill patients with acute coronary syndrome: a retrospective cohort study from MIMIC-IV.

BACKGROUND: The stress hyperglycemia ratio (SHR) is increasingly recognized as a reliable biomarker for adverse outcomes. However, its prognostic valu...

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 ...

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...

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...

Advancing stroke prevention in atrial fibrillation: a systematic review of machine learning-based risk prediction models.

BACKGROUND: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and confers a four to fivefold increase in ischemic stroke risk, ...

Gene expression integration and similarity score based modeling improve risk stratification in idiopathic venous thrombophilia.

BACKGROUND: Idiopathic venous thromboembolism (VTE) occurs in the absence of provoking factors, limiting the efficacy of current risk stratification. ...

[Position paper of the German Society of Cardiology-quality criteria for performing catheter ablation of atrial fibrillation: executive summary].

The updated German Society of Cardiology (DGK) position paper on catheter ablation of atrial fibrillation (AF) [1] presents the current evidence, tech...

Formulaic and novel language dissociate in Alzheimer's clinical syndrome: evidence for the Dual-Process Model.

INTRODUCTION: Spontaneous speech is commonly disrupted in persons with Alzheimer's disease (AD) and/or Alzheimer's clinical syndrome (ACS). Importantl...