AIMC Topic: Body Mass Index
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Association between muscle mass assessed by an artificial intelligence-based ultrasound imaging system and quality of life in patients with cancer-related malnutrition.
Nutrition (Burbank, Los Angeles County, Calif.)
Mar 12, 2025
INTRODUCTION: Emerging evidence suggests that diminished skeletal muscle mass is associated with lower health-related quality of life (HRQOL) in individuals with cancer. There are no studies that we know of in the literature that use ultrasound syste...
Artificial intelligence for weight estimation in paediatric emergency care.
BMJ paediatrics open
Mar 12, 2025
OBJECTIVE: To develop and validate a paediatric weight estimation model adapted to the characteristics of the Spanish population as an alternative to currently extended methods.
Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States.
Diabetes, obesity & metabolism
Mar 11, 2025
AIMS: Numerous risk factors for the development of obesity have been identified, yet the aetiology is not well understood. Traditional statistical methods for analysing observational data are limited by the volume and characteristics of large dataset...
Prediction of malnutrition in kids by integrating ResNet-50-based deep learning technique using facial images.
Scientific reports
Mar 6, 2025
In recent times, severe acute malnutrition (SAM) in India is considered a serious issue as per UNICEF 2022 records. In that record, 35.5% of children under age 5 are stunted, 19.3% are wasted, and 32% are underweight. Malnutrition, defined as these t...
An early prediction model for gestational diabetes mellitus created using machine learning algorithms.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Mar 4, 2025
OBJECTIVE: To investigate high-risk factors for gestational diabetes mellitus (GDM) in early pregnancy through an analysis of demographic and clinical data, and to develops a machine-learning-based prediction model to enhance early diagnosis and inte...
Development and clinical evaluation of an AI-assisted respiratory state classification system for chest X-rays: A BMI-Specific approach.
Computers in biology and medicine
Feb 16, 2025
PURPOSE: In this study, we aimed to develop and clinically evaluate an artificial intelligence (AI)-assisted support system for determining inhalation and exhalation states on chest X-ray images, focusing on the specific challenge of respiratory stat...
Factors associated with underweight, overweight, and obesity in Chinese children aged 3-14 years using ensemble learning algorithms.
Journal of global health
Feb 7, 2025
BACKGROUND: Factors underlying the development of childhood underweight, overweight, and obesity are not fully understood. Traditional models have drawbacks in handling large-scale, high-dimensional, and nonlinear data. In this study, we aimed to ide...
Transfer Learning Prediction of Early Exposures and Genetic Risk Score on Adult Obesity in Two Minority Cohorts.
Prevention science : the official journal of the Society for Prevention Research
Feb 6, 2025
Due to ethnic heterogeneity in genetic architecture, genetic risk score (GRS) constructed within the European population generally possesses poor portability in underrepresented non-European populations, but substantial genetic similarity exists acro...
Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches.
BMC medical informatics and decision making
Jan 31, 2025
BACKGROUND: The aim of this study was to evaluate the potential models to determine the most important anthropometric factors associated with type 2 diabetes mellitus (T2DM).
Machine learning web application for predicting varicose veins utilizing global prevalence data.
Phlebology
Jan 29, 2025
AimThis study aimed to develop a web-based machine learning (ML) model to predict the lifetime likelihood of developing varicose veins using global disease prevalence data.MethodsWe utilized data from a systematic review, registered under PROSPERO (C...
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