Artificial intelligence (AI) is an overarching term that encompasses a set of computational approaches that are trained through generalised learning to autonomously execute specific tasks. AI is a rapidly expanding field in medicine. In particular cardiology, with its high reliance on numerical patient data in decision making, has great potential to benefit from AI. Types of AI, including neural networks and computer vision, can dramatically change the day-to-day workflow of cardiologists, primarily through integration in diagnostic imaging modalities, periprocedural planning, electronic health record analysis and patient monitoring. Healthcare systems will undoubtedly become more automated and shift to more AI-driven methods to improve efficiency and reduce cost. Patients in the end will benefit from these changes with improved diagnostic accuracy, better tailored treatments resulting in a greater quality and quantity of life. In this article, we will describe some of the fundamental principles underlying AI that physicians should have an understanding of, along with current clinical applications.
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http://dx.doi.org/10.1111/imj.15562 | DOI Listing |
Stroke
January 2025
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, China. (X.X., X.L., Y.P., Yufei Wei, Y.J., M.W., J.J., X.M., Yilong Wang, Yongjun Wang, L.L.).
Background: We performed a prespecified subgroup analysis of the CATIS-2 trial (China Antihypertensive Trial in Acute Ischemic Stroke II) to compare the effect of early versus delayed antihypertensive treatment on death and disability in patients with and without medical history of hypertension.
Methods: CATIS-2 is a multicenter randomized clinical trial conducted in 106 hospitals in China. The trial randomized 4810 patients with acute ischemic stroke within 24 to 48 hours of symptom onset and elevated systolic blood pressure between 140 and <220 mm Hg to receive antihypertensive treatment immediately after randomization or to discontinue antihypertensive medications for 7 days and then receive treatment on day 8.
Emergencias
December 2024
Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seúl, República de Corea. Department of Digital Health, SAIHST, Sungkyunkwan University, Seúl, República de Corea.
Objective: To develop a Metabolic Derangement Score (MDS) based on parameters available after initial testing and assess the score's ability to predict survival after out-of hospital cardiac arrest (OHCA) and the likely usefulness of extracorporeal life support (ECLS).
Methods: A total of 5100 cases in the Korean Cardiac Arrest Research Consortium registry were included. Patients' mean age was 67 years, and 69% were men.
Background: Diabetic kidney disease (DKD) is one of the typical complications of type 2 diabetes (T2D), with approximately 10 % of DKD patients experiencing a Rapid decline (RD) in kidney function. RD leads to an increased risk of poor outcomes such as the need for dialysis. Albuminuria is a known kidney damage biomarker for DKD, yet RD cases do not always show changes in albuminuria, and the exact mechanism of RD remains unclear.
View Article and Find Full Text PDFMiddle East J Dig Dis
October 2024
Department of Health Information Technology, Ferdows Faculty of Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran.
Background: Patients with inflammatory bowel disease (IBD) require lifelong treatment, which significantly impacts their quality of life. Self-management of this disease is an effective factor in managing chronic conditions and improving patients' quality of life. The use of mobile applications is a novel approach to providing self-management models and healthcare services for patients with IBD.
View Article and Find Full Text PDFJ Taibah Univ Med Sci
December 2024
King Saud Medical City, Ministry of Health & College of Medicine, Alfaisal University Riyadh, KSA.
KSA is transforming its healthcare system by developing and implementing Clinical Practice Guidelines (CPGs), a tool designed to improve patient outcomes, standardize care, and facilitate evidence-based decision-making. CPGs are crucial in addressing healthcare disparities, thereby promoting health equity and patient experience. They are integral to KSA's healthcare transformation agenda.
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