Abstract Background: Achieving safe glycemic targets in intensive care remains difficult due to rapidly changing physiology, treatment effects, and measurement noise. Objective: We systematically review artificial-intelligence (AI) methods for ICU..
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Abstract OBJECTIVES Extracorporeal membrane oxygenation (ECMO) is a life-saving therapy for severe cardiopulmonary failure, but structured training remains constrained by costs, logistics, and the absence of validated high-fidelity simulators. This..
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Abstract Background: Harlequin syndrome, also referred to as differential hypoxemia or North South syndrome, is a critical yet underrecognized complication of venoarterial extracorporeal membrane oxygenation and hybrid configurations such as ECpella...
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Abstract Objectives To evaluate the effectiveness of Artificial Intelligence (AI) in improving clinical outcomes in Extracorporeal Membrane Oxygenation (ECMO) management, focusing on ECMO initiation, prognosis, and complications. Methods A meta-analysis following..
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Abstract Introduction The increasing integration of Artificial Intelligence (AI) and Virtual Reality (VR) in healthcare education offers innovative ways to enhance collaborative learning and improve patient safety. This narrative review..
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Abstract Assisted artificial intelligence (A-AI) has rapidly become a gold standard approach for conducting data analysis and medical writing []. From executing complex statistical tasks to extracting relevant information and..
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Introduction Artificial Intelligence (AI) is rapidly transforming perfusion, particularly in cardiopulmonary bypass (CPB) and extracorporeal membrane oxygenation (ECMO). By leveraging machine learning (ML) and real-time data analysis, AI enhances decision-making,..
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Abstract Background Despite advancements in imaging technologies, including CT scans and MRI, these modalities may still fail to capture intricate details of congenital heart defects accurately. Virtual 3D models have..
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Abstract Introduction On January 27, 2025, DeepSeek-R1, a new Generative AI model, was introduced and rapidly gained adoption, taking over the user market to become the No.1 downloaded AI app , , ...
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Abstract Introduction Congenital heart disease (CHD) represents the most common group of congenital anomalies, constitutes a significant contributor to the burden of non-communicable diseases, highlighting the critical need for improved..
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Abstract Background: Reading medical papers is a challenging and time-consuming task for doctors, especially when the papers are long and complex. A tool that can help doctors efficiently process and..
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Abstract John McCarthy first used the term artificial intelligence (AI) in a conference at Dartmouth College in 1956. He discussed “the science and engineering of making intelligent machines.” This paved..
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Abstract Artificial intelligence (AI) is rapidly emerging in healthcare, yet applications in surgery remain relatively nascent. Here we review the integration of AI in the field of surgery, centering our..
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Abstract Artificial intelligence (AI) is a transformative technology with many benefits, but also risks when applied to healthcare and cardiac surgery in particular. Surgeons must be aware of AI and..
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Abstract The recent introduction of ChatGPT, an advanced, easy-to-use, and freely available artificial intelligence (AI) program, created new possibilities across many industries and professions including healthcare simulation. ChatGPT has the..
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Abstract What are AI, Machine Learning, and Artificial Neural Networks? Medical publishing in AI has increased exponentially over the last few years.7 Artificial intelligence is a broad term that represents the..
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Abstract Artificial intelligence has the potential to improve the care that is given to patients; however, the predictive models created are only as good as the base data used in..
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Abstract Purpose: Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is a complex and high-risk life support modality used in severe cardiorespiratory failure. ECMO survival scores are used clinically for patient prognostication and..
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Abstract OBJECTIVES This study aims to improve the early detection of cardiac surgery-associated acute kidney injury using artificial intelligence-based algorithms. METHODS Data from consecutive patients undergoing cardiac surgery between 2008..
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Abstract Objective Evidence-based medicine (EBM) is a decision-making process based on the conscious and judicious use of the best available scientific evidence. However, the exponential increase in the amount of..
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Abstract Big Data, and the derived analysis techniques, such as artificial intelligence and machine learning, have been considered a revolution in the modern practice of medicine. Big Data comes from..
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Abstract This article introduces management algorithms to support operators in choosing the best strategy for metabolic management during cardiopulmonary bypass using artificial intelligence systems. We developed algorithms for the identification..
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Abstract Artificial intelligence (AI) and machine learning (ML) are poised to transform the way health care is delivered. AI is the use of computers to simulate intelligent tasks typically performed..
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Abstract Innovations in healthcare are growing exponentially, resulting in improved quality of and access to care, as well as rising societal costs of care and variable reimbursement. In recent years,..
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Abstract Objective: Risk assessment tools typically used in congenital heart surgery (CHS) assume that various possible risk factors interact in a linear and additive fashion, an assumption that may not..
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Abstract Effectiveness of computer vision techniques has been demonstrated through a number of applications, both within and outside healthcare. The operating room environment specifically is a setting with rich data..
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