Publications by authors named "D R Leone"

Artificial intelligence (AI) is revolutionizing healthcare by offering innovative solutions for diagnosis, treatment, and patient management. Only recently has the field of pediatric cardiology begun to explore the use of deep learning methods to analyze electrocardiogram (ECG) data, aiming to enhance diagnostic accuracy, expedite workflows, and improve patient outcomes. This review examines the current state of AI-enhanced ECG interpretation in pediatric cardiology applications, drawing insights from adult AI-ECG research given the progress in this field.

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Blood pressure (BP) variability (BPV) is an independent predictor of cardiovascular (CV) events. The role of BPV in defining risk of cancer therapy-related cardiovascular toxicity (CTR-CVT) is currently unknown. The aims of this study were: (i) to evaluate BPV in a population of patients with Multiple Myeloma, undergoing proteasome inhibitors therapy; (ii) to assess the predictive value of BPV for CTR-CVT; (iii) to analyze clusters of subjects based on BPV.

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Fetal echocardiography (FE) is recommended for parents with congenital heart disease (pCHD) due to a 3-6% recurrence risk of congenital heart disease (CHD). This study aimed to evaluate the cost of FE for detecting neonatal CHD in pCHD. FE data were collected between 12/2015 and 12/2022.

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Background: Heart failure with preserved ejection fraction (HFpEF) is a high prevalence condition, with high rates of hospitalization and mortality. Arterial hypertension is the main risk factor for HFpEF. Among hypertensive patients, alterations in cardiac and vascular morphology identify hypertension-mediated organ damage (HMOD).

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