[HTML][HTML] The role of genetic and epigenetic factors in determining the risk of spinal fragility fractures: new insights in the management of spinal osteoporosis

V Himič, N Syrmos, GKI Ligarotti, S Kato… - … Imaging in Medicine …, 2023 - ncbi.nlm.nih.gov
Osteoporosis predisposes patients to spinal fragility fractures. Imaging plays a key role in the
diagnosis and prognostication of these osteoporotic vertebral fractures (OVF). However, the …

New horizons: artificial intelligence tools for managing osteoporosis

HP Dimai - The Journal of Clinical Endocrinology & Metabolism, 2023 - academic.oup.com
Osteoporosis is a disease characterized by low bone mass and microarchitectural
deterioration leading to increased bone fragility and fracture risk. Typically, osteoporotic …

Development and validation of a feature-based broad-learning system for opportunistic osteoporosis screening using lumbar spine radiographs

B Zhang, Z Chen, R Yan, B Lai, G Wu, J You, X Wu… - Academic …, 2024 - Elsevier
Rationale and Objectives Osteoporosis is primarily diagnosed using dual-energy X-ray
absorptiometry (DXA); yet, DXA is significantly underutilized, causing osteoporosis, an …

A robust multi-utility neural network technique integrated with discriminators for bone health decisioning to facilitate clinical-driven processes

K Ramaraj, G Amiya, MP Rajasekaran… - Research on Biomedical …, 2023 - Springer
Purpose Osteoporosis (OP) is a malformation of the bones caused by the loss of bone mass
and its mineral density, and also deterioration in bone quality or structures, causing an …

[HTML][HTML] Deep learning-assisted knee osteoarthritis automatic grading on plain radiographs: the value of multiview X-ray images and prior knowledge

W Li, Z Xiao, J Liu, J Feng, D Zhu, J Liao… - … Imaging in Medicine …, 2023 - ncbi.nlm.nih.gov
Background Knee osteoarthritis (OA) is harmful to people's health. Effective treatment
depends on accurate diagnosis and grading. This study aimed to assess the performance of …

Machine learning and radiomics of bone scintigraphy: their role in predicting recurrence of localized or locally advanced prostate cancer

YD Wang, CP Huang, YR Yang, HC Wu, YJ Hsu… - Diagnostics, 2023 - mdpi.com
Background: Machine-learning (ML) and radiomics features have been utilized for survival
outcome analysis in various cancers. This study aims to investigate the application of ML …

[PDF][PDF] A dual-selective channel attention network for osteoporosis prediction in computed tomography images of lumbar spine

L Xue, Y Hou, S Wang, C Luo, ZY Xia… - … Transactions on AI …, 2022 - library.acadlore.com
Osteoporosis is a common systemic bone disease with insidious onset and low treatment
efficiency. Once it occurs, it will increase bone fragility and lead to fractures. Computed …

Predicting osteoporosis from kidney-ureter-bladder radiographs utilizing deep convolutional neural networks

TY Yen, CS Ho, YC Pei, TY Fan, SY Chang, CF Kuo… - Bone, 2024 - Elsevier
Osteoporosis is a common condition that can lead to fractures, mobility issues, and death.
Although dual-energy X-ray absorptiometry (DXA) is the gold standard for osteoporosis, it is …

Application of Artificial Intelligence Methods on Osteoporosis Classification with Radiographs—A Systematic Review

RW Liu, W Ong, A Makmur, N Kumar, XZ Low… - Bioengineering, 2024 - mdpi.com
Simple Summary Osteoporosis is a major global health problem with substantial economic
and psychosocial repercussions. Underdiagnosis of osteoporosis is prevalent. The dual …

Automated graded prognostic assessment for patients with hepatocellular carcinoma using machine learning

M Gross, SP Haider, T Ze'evi, S Huber, S Arora… - European …, 2024 - Springer
Background Accurate mortality risk quantification is crucial for the management of
hepatocellular carcinoma (HCC); however, most scoring systems are subjective. Purpose To …