Transfusion medicine hackathon: Nurturing the innovative ideas to revolutionize voluntary blood donation.

Background And Objective: Blood transfusion is an essential component of health care. However, several issues can hamper the promotion and sustainability of voluntary blood donation programs. This article is about a hackathon in the field of transfusion medicine that was designed to stimulate original ideas to promote voluntary blood donation.

Automated proximal coronary artery calcium identification using artificial intelligence: advancing cardiovascular risk assessment.

Aims: Proximal coronary artery calcium (CAC) may improve prediction of major adverse cardiac events (MACE) beyond the CAC score, particularly in patients with low CAC burden. We investigated whether the proximal CAC can be detected on gated cardiac computer tomography (CT) and whether it provides prognostic significance with artificial intelligence (AI).

Methods And Results: A total of 2016 asymptomatic adults with baseline CAC CT scans from a single site were followed up for MACE for 14 years.

AI-derived automated quantification of cardiac chambers and myocardium from non-contrast CT: Prediction of major adverse cardiovascular events in asymptomatic subjects.

Background And Aims: The significance of left ventricular mass and chamber volumes from non-contrast computed tomography (CT) for predicting major adverse cardiovascular events (MACE) has not been studied. Our objective was to evaluate the role of artificial intelligence-enabled multi-chamber cardiac volumetry from non-contrast CT for long-term risk stratification in asymptomatic subjects without known coronary artery disease.

Methods: Our study included 2022 asymptomatic individuals (55.

Evaluating AI proficiency in nuclear cardiology: Large language models take on the board preparation exam.

Background: Previous studies evaluated the ability of large language models (LLMs) in medical disciplines; however, few have focused on image analysis, and none specifically on cardiovascular imaging or nuclear cardiology. This study assesses four LLMs-GPT-4, GPT-4 Turbo, GPT-4omni (GPT-4o) (Open AI), and Gemini (Google Inc.)-in responding to questions from the 2023 American Society of Nuclear Cardiology Board Preparation Exam, reflecting the scope of the Certification Board of Nuclear Cardiology (CBNC) examination.

Utility of Mechanistic Target of Rapamycin Inhibitors in Cardiac Sarcoidosis.

Background: Cardiac sarcoidosis is an uncommon but potentially devastating manifestation of sarcoidosis, which is a multisystem inflammatory granulomatous disease. Although corticosteroids are the mainstay of treatment, given the number of complications associated with their long-term use, there is increasing interest in the use of steroid-sparing agents. Recent basic and translational studies have suggested a role for the mechanistic target of rapamycin (mTOR) pathway in cardiac sarcoidosis.