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Advances in digital anthropometric body composition assessment: neural network algorithm prediction of appendicular lean mass.
European journal of clinical nutrition
Dec 23, 2023
Currently available anthropometric body composition prediction equations were often developed on small participant samples, included only several measured predictor variables, or were prepared using conventional statistical regression methods. Machin...
Applying Machine Learning Analysis Based on Proximal Femur of Abdominal Computed Tomography to Screen for Abnormal Bone Mass in Femur.
Academic radiology
Nov 15, 2023
RATIONALE AND OBJECTIVES: To evaluate the performance of machine learning analysis based on proximal femur of abdominal computed tomography (CT) scans in screening for abnormal bone mass in femur.
Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning.
The British journal of radiology
Oct 24, 2023
OBJECTIVE: To develop and evaluate a fully automated method based on deep learning and phantomless internal calibration for bone mineral density (BMD) measurement and opportunistic low BMD (osteopenia and osteoporosis) screening using chest low-dose ...
Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women.
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Sep 20, 2023
UNLABELLED: While FRAX with BMD could be more precise in estimating the fracture risk, DL-based models were validated to slightly reduce the number of under- and over-treated patients when no BMD measurements were available. The validated models coul...
Comparison of computed tomography and dual-energy X-ray absorptiometry in the evaluation of body composition in patients with obesity.
Frontiers in endocrinology
Jun 26, 2023
OBJECTIVE: a) To evaluate the accuracy of the pre-existing equations (based on cm2 provided by CT images), to estimate in kilograms (Kg) the body composition (BC) in patients with obesity (PwO), by comparison with Dual-energy X-ray absorptiometry (DX...
Prediction of osteoporosis using MRI and CT scans with unimodal and multimodal deep-learning models.
Diagnostic and interventional radiology (Ankara, Turkey)
Jun 13, 2023
PURPOSE: Osteoporosis is the systematic degeneration of the human skeleton, with consequences ranging from a reduced quality of life to mortality. Therefore, the prediction of osteoporosis reduces risks and supports patients in taking precautions. De...
Deep-Learning-Based Detection of Vertebral Fracture and Osteoporosis Using Lateral Spine X-Ray Radiography.
Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
May 4, 2023
Osteoporosis and vertebral fractures (VFs) remain underdiagnosed. The addition of deep learning methods to lateral spine radiography (a simple, widely available, low-cost test) can potentially solve this problem. In this study, we develop deep learni...
Validity and reliability of a mobile digital imaging analysis trained by a four-compartment model.
Journal of human nutrition and dietetics : the official journal of the British Dietetic Association
Dec 7, 2022
BACKGROUND: Digital imaging analysis (DIA) estimates collected from mobile applications comprise a novel technique that can collect body composition estimates remotely without the inherent restrictions of other research-grade devices. However, the ac...
Visual body composition assessment methods: A 4-compartment model comparison of smartphone-based artificial intelligence for body composition estimation in healthy adults.
Clinical nutrition (Edinburgh, Scotland)
Sep 29, 2022
BACKGROUND & AIMS: Visual body composition (VBC) estimates produced from smartphone-based artificial intelligence represent a user-friendly and convenient way to automate body composition remotely and without the inherent geographical and monetary re...
Deep learning for screening primary osteopenia and osteoporosis using spine radiographs and patient clinical covariates in a Chinese population.
Frontiers in endocrinology
Sep 13, 2022
PURPOSE: Many high-risk osteopenia and osteoporosis patients remain undiagnosed. We proposed to construct a convolutional neural network model for screening primary osteopenia and osteoporosis based on the lumbar radiographs, and to compare the diagn...
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