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Evaluation of a content-based image retrieval system for radiologists in high-resolution CT of interstitial lung diseases.
Eur Radiol Exp
January 2025
Division of Cardiothoracic Imaging, Department of Radiology and Imaging Sciences, Emory University Hospital, Atlanta, GA, USA.
Background: This retrospective study aims to evaluate the impact of a content-based image retrieval (CBIR) application on diagnostic accuracy and confidence in interstitial lung disease (ILD) assessment using high-resolution computed tomography CT (HRCT).
Methods: Twenty-eight patients with verified pattern-based ILD diagnoses were split into two equal datasets (1 and 2). The images were assessed by two radiology residents (3rd and 5th year) and one expert radiologist in four sessions.
Machine learning applications in healthcare clinical practice and research.
World J Clin Cases
January 2025
Department of Gastroenterology, Laiko General Hospital, National and Kapodistrian University of Athens, Athens 11527, Greece.
Machine learning (ML) is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis, thus creating machines that can complete tasks otherwise requiring human intelligence. Among its various applications, it has proven groundbreaking in healthcare as well, both in clinical practice and research. In this editorial, we succinctly introduce ML applications and present a study, featured in the latest issue of the .
View Article and Find Full Text PDFRetraction notice to "Bioremediation of polycyclic aromatic hydrocarbons: An updated microbiological review" [Chemosphere 328 (2023) 138498].
Chemosphere
February 2025
School of Engineering, Lebanese American University, Byblos, Lebanon; University Centre for Research & Development, Department of Civil Engineering, Chandigarh University, Mohali, 140103, India.
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal).
View Article and Find Full Text PDFReference ranges for complete blood count in children and adolescents with Down syndrome.
Front Pediatr
December 2024
Pediatrics, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy.
Introduction: Down syndrome (DS) is linked to unique hematopoietic characteristics that affect complete blood count (CBC) parameters. Accurate reference ranges are essential for proper CBC interpretation in this population.
Methods: This retrospective study analyzed 2,627 CBCs from 481 DS patients, aged 31 days to 18 years, at a tertiary care center in Italy.
Evaluating post-cardiac arrest blood pressure thresholds associated with neurologic outcome in children: Insights from the pediRES-Q database.
Resuscitation
December 2024
Department of Pediatrics, Division of Critical Care Medicine, Kravis Children's Hospital, Icahn School of Medicine at Mount Sinai, 1184 5th Ave, New York, NY 10029, USA.
Background: Current Pediatric Advanced Life Support Guidelines recommend maintaining blood pressure (BP) above the 5th percentile for age following return of spontaneous circulation (ROSC) after cardiac arrest (CA). Emerging evidence suggests that targeting higher thresholds, such as the 10th or 25th percentiles, may improve neurologic outcomes. We aimed to evaluate the association between post-ROSC BP thresholds and neurologic outcome, hypothesizing that maintaining mean arterial pressure (MAP) and systolic blood pressure (SBP) above these thresholds would be associated with improved outcomes at hospital discharge.
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