Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized care. Alternatives like left atrial appendage closure devices lower stroke risk with fewer nonprocedural blee...
BACKGROUND: Dual antiplatelet therapy (DAPT) after coronary artery bypass grafting (CABG), although might be protective for ischemic events, can lead to varying degrees of bleeding, resulting in serious clinical events, including death. This study ai...
BACKGROUND: Pulmonary hemorrhage (PH) in respiratory distress syndrome (RDS) in extremely preterm infants exhibits a high mortality rate and poor long-term outcomes. The aim of the present study was to develop a machine learning (ML) predictive model...
Journal of the American Heart Association
Sep 30, 2024
BACKGROUND: After coronary stent implantation, prolonged dual antiplatelet therapy (DAPT) increases bleeding risk, requiring personalization of DAPT duration. The aim of this study was to develop and validate a machine learning model to predict optim...
The journal of trauma and acute care surgery
Sep 27, 2024
BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly after injury. This has profound implications for resuscitation from hemorrhagic shock, as ATC is associated with increased risk for massive transfusi...
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Sep 14, 2024
PURPOSE: We developed a predictive model to assess the risk of major bleeding (MB) within 6 months of primary venous thromboembolism (VTE) in cancer patients receiving anticoagulant treatment. We also sought to describe the prevalence and incidence o...
Primary immune thrombocytopenia (ITP) is an autoimmune bleeding disorder, and chemokines have been shown to be dysregulated in autoimmune disorders. We conducted a prospective analysis to identify potential chemokines that could enhance the diagnosti...
INTRODUCTION: Artificial intelligence and large language models (LLMs) have emerged as potentially disruptive technologies in healthcare. In this study GPT-3.5, an accessible LLM, was assessed for its accuracy and reliability in performing guideline-...
The journal of trauma and acute care surgery
May 9, 2024
BACKGROUND: Hemorrhage is a leading cause of preventable death in trauma. Accurately predicting a patient's blood transfusion requirement is essential but can be difficult. Machine learning (ML) is a field of artificial intelligence that is emerging ...
BACKGROUND: The accuracy of available prediction tools for clinical outcomes in patients with atrial fibrillation (AF) remains modest. Machine Learning (ML) has been used to predict outcomes in the AF population, but not in a population entirely on a...
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