Artificial Intelligence in Skeletal Health
Digital Collections | First published: 31 August 2023 | Last updated: 28 September 2023
By leveraging advanced algorithms and data analytics, artificial intelligence offers unprecedented insights and diagnostic innovations, propelling the field of skeletal health into a new era. This collection of articles from JBMR showcase the use of AI in the field of bone, mineral, and musculoskeletal science.
Table of Contents
Open Access
Towards Improved Identification of Vertebral Fractures in Routine Computed Tomography (CT) Scans: Development and External Validation of a Machine Learning Algorithm
Joeri Nicolaes et al.
Journal of Bone and Mineral Research
First Published: 25 September 2023
Vertebral fractures are the landmark of osteoporosis and are associated with increased risk of further fractures. Yet they commonly go undiagnosed, and the underlying osteoporosis untreated. We developed a machine learning algorithm for automated vertebral fracture detection and demonstrated strong performance on an external validation set of 2000 CT scans. This method can improve the identification and reporting of vertebral fractures by opportunistically screening for them in routine CT scans.
Open Access
A Fracture Risk Assessment Tool for High Resolution Peripheral Quantitative Computed Tomography
Danielle E. Whittier et al.
Journal of Bone and Mineral Research
First Published: 03 May 2023
Open Access
Hip Fracture Risk Assessment in Elderly and Diabetic Patients: Combining Autonomous Finite Element Analysis and Machine Learning
Zohar Yosibash et al.
Journal of Bone and Mineral Research
First Published: 27 March 2023
Artificial Intelligence in Musculoskeletal Imaging: A Paradigm Shift
Joseph E Burns et al.
Journal of Bone and Mineral Research
First Published: 09 August 2019
Machine Learning Solutions for Osteoporosis—A Review
Julien Smets et al.
Journal of Bone and Mineral Research
First Published: 22 March 2021
Clinical Utility of Computer-Aided Diagnosis of Vertebral Fractures From Computed Tomography Images
Nithin Kolanu et al.
Journal of Bone and Mineral Research
First Published: 04 August 2020
Opportunistic Osteoporosis Screening Using Chest Radiographs With Deep Learning: Development and External Validation With a Cohort Dataset
Miso Jang et al.
Journal of Bone and Mineral Research
First Published: 23 November 2021
Open Access
Deep-Learning-Based Detection of Vertebral Fracture and Osteoporosis Using Lateral Spine X-Ray Radiography
Namki Hong et al.
Journal of Bone and Mineral Research
First Published: 10 April 2023
Open Access
Automated Opportunistic Osteoporosis Screening in Routine Computed Tomography of the Spine: Comparison With Dedicated Quantitative CT
Nico Sollmann et al.
Journal of Bone and Mineral Research
First Published: 22 May 2022
Open Access
High Bone Mass Disorders: New Insights From Connecting the Clinic and the Bench
Dylan J.M. Bergen et al.
Journal of Bone and Mineral Research
First Published: 26 September 2022
Open Access
Spatial Lipidomic Profiling of Mouse Joint Tissue Demonstrates the Essential Role of PHOSPHO1 in Growth Plate Homeostasis
Jordan Tzvetkov et al.
Journal of Bone and Mineral Research
First Published: 23 February 2023
Differentiation of Induced Pluripotent Stem Cells Into Chondrocytes: Methods and Applications for Disease Modeling and Drug Discovery
Pauline De Kinderen et al.
Journal of Bone and Mineral Research
First Published: 06 February 2022
Open Access
Quantitating Age-Related BMD Textural Variation from DXA Region-Free-Analysis: A Study of Hip Fracture Prediction in Three Cohorts
Mohsen Farzi et al.
Journal of Bone and Mineral Research
First Published: 24 June 2022
