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Background: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening complication in patients with acute myocardial infarction (AMI), significantly affecting prognosis during hospitalization. Early identification of high-risk patients is essential to reduce complications, improve outcomes, and guide clinical decision-making.

Objective: This study aimed to develop and validate a machine learning (ML)-based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support.

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A comparative analysis of CNNs and LSTMs for ECG-based diagnosis of arrythmia and congestive heart failure.

Comput Methods Biomech Biomed Engin

January 2025

Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India.

Cardiac arrhythmias are major global health concern and their early detection is critical for diagnosis. This study comprehensively evaluates the effectiveness of CNNs and LSTMs for the classification of cardiac arrhythmias, considering three PhysioNet datasets. ECG records are segmented to accommodate around ∼10s of ECG data.

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The ossa cordis (OC), or cardiac bone, is a bony structure within the cardiac skeleton of mammals, believed to maintain heart shape during systole and enhance contraction efficiency. Found in large mammals, especially ruminants, and has recently been described in chimpanzees; however, OC has not previously been described in humans. Herein, we present an incidental finding of OC in the heart of a 39-year-old man who suffered a stab wound to chest.

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Background: Psychological distress, such as depression and anxiety, impacts cardiovascular disease (CVD) prognosis and management. Illness comprehension is essential for effective treatment, but biases can lead to suboptimal outcomes. We explored psycho-cardiovascular disease (PCD) patient characteristics, with a specific focus on comprehension biases and treatment choices from patients' perspectives in China, to improve management strategies.

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Right ventricular myocardial infarction (RVMI) is a significant and distinct form of acute myocardial infarction associated with considerable morbidity and mortality. It occurs most commonly due to proximal right coronary artery obstruction, often in conjunction with inferior myocardial infarction. RVMI poses unique diagnostic and therapeutic challenges due to the anatomical and functional differences between the right and left ventricles.

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