The development of artificial intelligence (AI) began in the mid-20th century but has been rapidly accelerating in the past decade. Reflecting the development of digital health over the past few years, this trend is also seen in medicine. The field of cardiovascular medicine uses a wide variety and a large amount of biosignals, so there are many situations where AI can contribute. The development of AI is in progress for all aspects of the healthcare system, including the prevention, screening, and treatment of diseases and the prediction of the prognosis. AI is expected to be used to provide specialist-level medical care, even in a situation where medical resources are scarce. However, like other medical devices, the concept and mechanism of AI must be fully understood when used; otherwise, it may be used inappropriately, resulting in detriment to the patient. Therefore, it is important to understand what we need to know as a cardiologist handling AI. This review introduces the basics and principles of AI, then shows how far the current development of AI has come, and finally gives a brief introduction of how to start the AI development for those who want to develop their own AI.
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http://dx.doi.org/10.1016/j.jjcc.2021.11.017 | DOI Listing |
Int J Retina Vitreous
January 2025
Fondation Asile des Aveugles, Department of Ophthalmology, Jules-Gonin Eye Hospital, University of Lausanne, Avenue de France 54, Lausanne, 1001, Switzerland.
Background: This study evaluates the efficacy of intravitreal Faricimab in reducing pigment epithelium detachment (PED) and fluid volumes in both treatment-naïve eyes and eyes unresponsive to anti-VEGF mono-therapies, all diagnosed with type 1 macular neovascularization (T1 MNV) over a period of 12-month.
Methods: A retrospective, single-center cohort study was conducted at the Jules Gonin Eye Hospital, Lausanne, Switzerland. Clinical records of treatment-naïve and non-responder switch patients presenting T1 MNV secondary to neovascular age-related macular degeneration (nAMD) from September 2022 to March 2023 were reviewed.
Orphanet J Rare Dis
January 2025
Laboratory of Metabolic Diseases, Department of Laboratory Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Postbus, Groningen, 30001 - 9700 RB, the Netherlands.
Background: Glycogen storage disease (GSD) Ia is an ultra-rare inherited disorder of carbohydrate metabolism. Patients often present in the first months of life with fasting hypoketotic hypoglycemia and hepatomegaly. The diagnosis of GSD Ia relies on a combination of different biomarkers, mostly routine clinical chemical markers and subsequent genetic confirmation.
View Article and Find Full Text PDFJ Cell Mol Med
January 2025
Department of Andrology, The First Hospital of Jilin University, Changchun, China.
Prostate cancer (PCa) is one of the most common cancers in men worldwide. Autophagy-related genes (ARGs) may play an important role in various biological processes of PCa. The aim of this study was to identify and evaluate autophagy-related features to predict clinical outcomes in patients with PCa.
View Article and Find Full Text PDFActa Neurochir (Wien)
January 2025
Department of Neurosurgery, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Background: The Focused Sylvian Approach (FSA) is a refined, minimally invasive technique for clipping small to medium-sized middle cerebral artery (MCA) aneurysms, prioritizing safety and aesthetics.
Method: The craniotomy remains confined to the superior temporal line, with the incision concealed within the temporal muscle. The Sylvian fissure is carefully dissected to preserve venous structures.
Neurosurg Rev
January 2025
Department of Radiology, Lanzhou University Second Hospital, Lanzhou, 730030, China.
To investigate the value of preoperative MRI features and ADC histogram analysis for evaluating tumor-infiltrating CD8+ T cells in meningiomas. In this single-center cross-sectional study, we conducted a retrospective analysis of clinical, imaging, and pathological data from 84 patients with meningioma and performed immunohistochemical staining to quantitatively evaluate CD8+ T cells. Using X-Tile software, we divided the patients into high-and low-CD8+ T cells groups based on cut-off values.
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