Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9397494 | PMC |
http://dx.doi.org/10.1002/jcsm.13020 | DOI Listing |
AJR Am J Roentgenol
January 2025
Associate Professor of Radiology, McMaster University, Department of Diagnostic Imaging, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences.
Urology
January 2025
Department of Urology, Mayo Clinic, Rochester, MN 55905. Electronic address:
Int Urol Nephrol
December 2024
Department of Thoracic Surgery, West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, 610041, Sichuan Province, China.
This paper evaluated the bibliometric study by Li et al. (Int Urol Nephrol, 2024) on machine learning in renal medicine. Although the study claims to summarize the forefront trends and hotspots in this field, several key issues require further clarification to effectively guide future research.
View Article and Find Full Text PDFWorld J Gastroenterol
December 2024
Division of Gastroenterology, Hepatology and Nutrition, The Hospital for Sick Children, Toronto M5G 1X8, Ontario, Canada.
In this article, we comment on the article by Qu and Li, focusing specifically on the non-invasive diagnostic approaches for metabolic dysfunction-associated steatotic liver disease (MASLD). MASLD is the most common chronic liver disease in children. Nearly half of pediatric MASLD cases progress to metabolic dysfunction-associated steatohepatitis at diagnosis, often with comorbidities like renal disease, hypertension, type 2 diabetes, and mental health disorders.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!