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Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study.
J Med Internet Res
January 2025
Department of Anesthesiology, Daping Hospital, Army Medical University, Chongqing, China.
Background: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic mortality. However, no studies have explored the risk factors, complications, and risk prediction of preoperative and postoperative traumatic coagulopathy (PPTIC) in patients with trauma.
View Article and Find Full Text PDFComparing three summary indices to assess diet quality of Canadian children: a call for consensus.
Front Nutr
January 2025
MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.
Purpose: The Healthy Eating Index-Canada 2015 (HEI-C 2015), Diet Quality Index-International (DQI-I), and Healthy Eating Food Index 2019 (HEFI-2019) are commonly used to summarize the quality of Canadian diets. This paper sought to compare these three diet quality indices with respect to their ability to capture diets of different quality in Canadian children and to discriminate between population subgroups.
Methods: Data were collected in school-based surveys from grade 4-6 students (9-12 years old) in western Canada through 24-h dietary recall in 2016 ( = 336), 2018 ( = 454), and 2020/2021 ( = 909).
AI Machine Learning-Based Diabetes Prediction in Older Adults in South Korea: Cross-Sectional Analysis.
JMIR Form Res
January 2025
1, Department of Health Administration, College of Software and Digital Healthcare Convergence, Yonsei University, Changjogwan, Yonseidae-gil 1, Wonju, 26493, Republic of Korea, +82 (0) 33-760-2257.
Background: Diabetes is prevalent in older adults, and machine learning algorithms could help predict diabetes in this population.
Objective: This study determined diabetes risk factors among older adults aged ≥60 years using machine learning algorithms and selected an optimized prediction model.
Methods: This cross-sectional study was conducted on 3084 older adults aged ≥60 years in Seoul from January to November 2023.
Infant and young child feeding practice status and its determinants in UAE: results from the MISC cohort.
Int Breastfeed J
January 2025
Department of Clinical Nutrition and Dietetics, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates.
Background: To evaluate breastfeeding and complementary feeding practices and their determinants among infants and young children in the United Arab Emirates using the 2021 WHO/UNICEF IYCF guidelines.
Methods: The Mother and Infant Study Cohort (MISC), is a prospective study of mothers recruited in their third gestational trimester and followed with their infants up to 18 months of age (n = 167). Data were collected at 3rd trimester, delivery, 2, 6, 12, and 18 months postpartum via questionnaires, review of medical records, anthropometric measurements, and 24-hour dietary recalls of the child's intake at 6, 12, and 18 months.
In clinical hand osteoarthritis research, self-reported pain questionnaires do not reflect the patient experience.
Rheumatology (Oxford)
January 2025
department of Rheumatology, Leiden University Medical Center, Leiden, the Netherlands.
Objective: Pain in hand osteoarthritis (OA) is evaluated with repeated pain questionnaires. It is unclear whether these questionnaires adequately capture changes in pain recalled by patients. This study investigated whether changes on pain questionnaires (real-time evaluation) correspond to recalled pain.
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