Necrotizing enterocolitis (NEC) is the most prevalent and potentially fatal intestinal injury mainly affecting premature infants, with significant long-term consequences for those who survive. This review explores the scale of the problem, highlighting advancements in epidemiology, the understanding of pathophysiology, and improvements in the prediction and diagnosis of this complex, multifactorial, and multifaced disease. Additionally, we focus on the potential role of metabolomics in distinguishing NEC from other conditions, which could allow for an earlier and more accurate classification of intestinal injuries in infants. By integrating metabolomic data with other diagnostic approaches, it is hoped to enhance our ability to predict outcomes and tailor treatments, ultimately improving care for affected infants.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11509608 | PMC |
http://dx.doi.org/10.3390/metabo14100521 | DOI Listing |
J Biomed Inform
January 2025
University of Manchester, United Kingdom.
Objective: Extracting named entities from clinical free-text presents unique challenges, particularly when dealing with discontinuous entities-mentions that are separated by unrelated words. Traditional NER methods often struggle to accurately identify these entities, prompting the development of specialised computational solutions. This paper systematically reviews and presents the methodologies developed for Discontinuous Named Entity Recognition in clinical texts, highlighting their effectiveness and the challenges they face.
View Article and Find Full Text PDFGerontologist
January 2025
School of Social Work, McGill University, Montreal, QC, Canada.
Background And Objectives: The paucity of research and policy on the impact of COVID-19 on the experiences of Black older adults in Canada and around the world has intensified the enduring impacts of racism on their health and well-being. To bridge this gap, our study explored the mental health of Black older adults in Montreal during the early period of the pandemic.
Research Design And Methods: Using an Afro-emancipatory mixed-method research design, we collected and analyzed data from three sources: a survey, focus group interview with service providers from Black community organizations, and individual interviews with Black older adults.
Nutrients
January 2025
Department of Computer Engineering, Inje University, Gimhae 50834, Republic of Korea.
Background: Food image recognition, a crucial step in computational gastronomy, has diverse applications across nutritional platforms. Convolutional neural networks (CNNs) are widely used for this task due to their ability to capture hierarchical features. However, they struggle with long-range dependencies and global feature extraction, which are vital in distinguishing visually similar foods or images where the context of the whole dish is crucial, thus necessitating transformer architecture.
View Article and Find Full Text PDFJ Clin Med
January 2025
Department of Psychology, Università degli Studi della Campania "L. Vanvitelli", 81100 Caserta, Italy.
Mental representation of spatial information relies on egocentric (body-based) and allocentric (environment-based) frames of reference. Research showed that spatial memory deteriorates as Alzheimer's disease (AD) progresses and that allocentric spatial memory is among the earliest impaired areas. Most studies have been conducted in static situations despite the dynamic nature of real-world spatial processing.
View Article and Find Full Text PDFLife (Basel)
January 2025
Department of Hand and Plastic Surgery, Thurgau Hospital Group, 8501 Frauenfeld, Switzerland.
AI, especially ChatGPT, is impacting healthcare through applications in research, patient communication, and training. To our knowledge, this is the first study to examine ChatGPT-4's ability to analyze images of lower leg defects and assesses its understanding of complex case reports in comparison to the performance of board-certified surgeons and residents. We conducted a cross-sectional survey in Switzerland, Germany, and Austria, where 52 participants reviewed images depicting lower leg defects within fictitious patient profiles and selected the optimal reconstruction techniques.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!