Abstract
Jessica L. Fairley, Mohit Kapoor, Divya Sharma
Abstract
Authors
Institutions
No ROR-resolved institution is linked to this work yet.
Provenance
crossref
Confidence 100%
pubmed
Confidence 98%
unpaywall
Confidence 95%
datacite
Confidence 0%
No local reference links have been materialized yet.
No local citing links have been materialized yet.
Global, regional, and national burden of osteoarthritis, 1990–2020 and projections to 2050: a systematic analysis for the Global Burden of Disease Study 2021
10.1016/s2665-9913(23)00163-7 · 2023
Osteoporosis
10.1016/s0140-6736(25)01385-6 · 2025
Characterizing mitochondrial features in osteoarthritis through integrative multi-omics and machine learning analysis
2024
LIANA+ provides an all-in-one framework for cell–cell communication inference
10.1038/s41556-024-01469-w · 2024
Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data
10.1016/j.ard.2025.01.012 · 2025
Data-driven identification of predictive risk biomarkers for subgroups of osteoarthritis using interpretable machine learning
10.1038/s41467-024-46663-4 · 2024
Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples
2024
Multi-omics integration and machine learning unveil FOXO3/SIRT1 axis as oxidative stress biomarkers and therapeutic targets in osteoporosis
2026
Multi-modal molecular determinants of clinically relevant osteoporosis subtypes
10.1038/s41421-024-00652-5 · 2024
Three-dimensional bone-image synthesis with generative adversarial networks
10.3390/jimaging10120318 · 2024
Radiomics grading of hand osteoarthritis severity using standard radiographs: results from the DIGICOD cohort
10.1016/j.joca.2026.05.009 · 2026
Clinical utility of foundation models in musculoskeletal MRI for biomarker fidelity and predictive outcomes
10.1038/s41746-026-02520-w · 2026
OncoGen.AI: an integrated platform for automated genomic analysis and reporting in precision oncology
10.1038/s41698-026-01578-9 · 2026
AI-derived bone mineral density from standard radiographs compared with DXA for fracture prediction in a 10-year real-world cohort study
10.1007/s00198-026-08100-8 · 2026
Identification of MEG3 and MAPK3 as potential therapeutic targets for osteoarthritis through multiomics integration and machine learning
2025
Performance of large language models in answering osteoporosis-related frequently asked questions: a systematic comparative evaluation based on international associations
10.1007/s00223-026-01546-2 · 2026
Comparative analysis of ChatGPT-4o mini, ChatGPT-4o and Gemini Advanced in the treatment of postmenopausal osteoporosis
10.1186/s12891-025-08601-3 · 2025
Generative artificial intelligence in osteoarthritis: a systematic scoping review of current applications and future directions
10.1016/j.joca.2026.03.001 · 2026
Large language models' performances regarding common patient questions about osteoarthritis: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and perplexity
10.1016/j.jshs.2024.101016 · 2025
Automated production of comparison tables for shared decision making: comparing a human-generated table (Option Grid), a search engine process, and outputs from four large language models
10.1016/j.pec.2025.109356 · 2026
Presentation suitability and readability of ChatGPT's medical responses to patient questions about on knee osteoarthritis
2025
Survey and analysis of hallucinations in large language models: attribution to prompting strategies or model behavior
10.3389/frai.2025.1622292 · 2025
When helpfulness backfires: LLMs and the risk of false medical information due to sycophantic behavior
10.1038/s41746-025-02008-z · 2025
Chatbot based on large Language model to improve adherence to exercise-based treatment in people with knee osteoarthritis: system development
10.3390/technologies13040140 · 2025
Preliminary evaluation of a large language model-powered chatbot for osteoporosis self-management education: formative randomized controlled trial
10.2196/85475 · 2026
The role of artificial intelligence large language models in personalized rehabilitation programs for knee osteoarthritis: an observational study
10.1007/s10916-025-02207-x · 2025
DeepTherapy: a mobile platform for osteoarthritis rehabilitation utilizing chain-of-thought reasoning and deep learning
10.18621/eurj.1672422 · 2025
Artificial intelligence used to diagnose osteoporosis from risk factors in clinical data and proposing sports protocols
10.1038/s41598-022-23184-y · 2022
Evaluating ChatGPT, Gemini and other Large Language Models (LLMs) in orthopaedic diagnostics: a prospective clinical study
10.1016/j.csbj.2024.12.013 · 2025
Quantitative evaluation of GPT-4’s performance on US and Chinese osteoarthritis treatment guideline interpretation and orthopaedic case consultation
10.1136/bmjopen-2023-082344 · 2024
Explainable multimodal knee osteoarthritis diagnosis from X-ray images using anomaly detection with clinical and structural biomarkers
10.1038/s41598-026-51211-9 · 2026
OAAgent: multimodal LLM agent for predicting knee osteoarthritis progression
10.1145/3721201.3721397 · 2025
Can artificial intelligence diagnose knee osteoarthritis?
2025
Large language models for efficient whole-organ MRI score-based reports and categorization in knee osteoarthritis
10.1186/s13244-025-01976-w · 2025
A deep learning model to predict knee osteoarthritis based on nonimage longitudinal medical record
10.2147/jmdh.s325179 · 2021
Early diagnosis of knee osteoarthritis with a natural language processing–driven approach based on clinician notes: development and validation study
10.2196/64536 · 2025
An automatic method for assessing spiking of tibial tubercles associated with knee osteoarthritis
10.3390/diagnostics12112603 · 2022
A discriminative shape-texture convolutional neural network for early diagnosis of knee osteoarthritis from X-ray images
10.1007/s13246-023-01256-1 · 2023
Automated machine learning-based prediction of the progression of knee pain, functional decline, and incidence of knee osteoarthritis in individuals at high risk of knee osteoarthritis: data from the osteoarthritis initiative study
2023
A deep learning method for predicting knee osteoarthritis radiographic progression from MRI
10.1186/s13075-021-02634-4 · 2021
Large language models propagate race-based medicine
10.1038/s41746-023-00939-z · doi-reference
Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: a systematic review
10.1002/ksa.70555 · doi-reference
Unveiling the black box: a systematic review of Explainable Artificial Intelligence in medical image analysis
10.1016/j.csbj.2024.08.005 · doi-reference
Development and validation of a multimodal AI-agent system for prognosis analysis of bladder urothelial carcinoma
10.1038/s41698-026-01415-z · doi-reference
A deep-learning-based RNA-seq germline variant caller
10.1093/bioadv/vbad062 · doi-reference
Generative AI for synthetic data across multiple medical modalities: a systematic review of recent developments and challenges
10.1016/j.compbiomed.2025.109834 · doi-reference
Towards a general-purpose foundation model for computational pathology
10.1038/s41591-024-02857-3 · doi-reference
Tensor-cell2cell v2 unravels coordinated dynamics of protein- and metabolite-mediated cell–cell communication
10.1093/bioinformatics/btaf667 · doi-reference
Single-cell RNA sequencing reveals that an imbalance in monocyte subsets rather than changes in gene expression patterns is a feature of postmenopausal osteoporosis
10.1093/jbmr/zjae065 · doi-reference
Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning
10.1186/s13018-025-05793-1 · doi-reference
Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence
10.1038/s41746-024-01076-x · doi-reference
Synthetic augmentation of cancer cell line multi-omic datasets using unsupervised deep learning
10.1038/s41467-024-54771-4 · doi-reference
Identify the potential target of efferocytosis in knee osteoarthritis synovial tissue: a bioinformatics and machine learning-based study
10.3389/fimmu.2025.1550794 · doi-reference
Machine learning identifies ferroptosis-related genes as potential diagnostic biomarkers for osteoarthritis
10.3389/fendo.2023.1198763 · doi-reference
Identification of immune-related risk genes in osteoarthritis based on bioinformatics analysis and machine learning
10.3390/jpm13020367 · doi-reference
Transcriptomic analyses and machine-learning methods reveal dysregulated key genes and potential pathogenesis in human osteoarthritic cartilage
10.1302/2046-3758.132.bjr-2023-0074.r1 · doi-reference
Machine learning-based predictive modeling, virtual screening and biological evaluation studies for identification of potential inhibitors of MMP-13
10.1080/07391102.2022.2117738 · doi-reference
Integration of multi-omics and machine learning to reveal the anti-osteoporosis effects of Hederagenin by inhibiting lipid peroxidation via the GPX4/p-STAT1/PTGS2 axis
10.1016/j.bcp.2026.117852 · doi-reference
Discovery of novel cathepsin K inhibitors for osteoporosis treatment using a deep learning-based strategy
10.1080/17460441.2025.2527686 · doi-reference
Deep learning-predicted dihydroartemisinin rescues osteoporosis by maintaining mesenchymal stem cell stemness through activating histone 3 lys 9 acetylation
10.1021/acscentsci.3c00794 · doi-reference
Multi-omics integrative analyses identified two endotypes of hip osteoarthritis
10.3390/metabo14090480 · doi-reference
Integrating bioinformatics and machine learning to identify biomarkers of branched chain amino acid related genes in osteoarthritis
10.1186/s12891-025-08779-6 · doi-reference
Plasma proteomic profiles predict individual future osteoarthritis risk
10.1002/art.43143 · doi-reference
Role and validation of Lactylation-Related gene markers in postmenopausal osteoporosis
10.1007/s12010-025-05216-1 · doi-reference
A metabolomics-driven machine learning model for osteoporosis risk prediction
10.1093/jbmrpl/ziag042 · doi-reference
Single-cell sequencing and machine learning-based prediction of spliceosome-associated factor 2 may represent potential targets for osteoarthritis
10.1016/j.ocarto.2026.100798 · doi-reference
Integrated multi-omics analyses reveal lipid metabolic signature in osteoarthritis
10.1016/j.jmb.2024.168888 · doi-reference
Synthetic data-enhanced classification of prevalent osteoporotic fractures using dual-energy X-Ray absorptiometry-based geometric and material parameters
10.3803/enm.2024.2211 · doi-reference
Context-aware deconvolution of cell-cell communication with Tensor-cell2cell
10.1038/s41467-022-31369-2 · doi-reference
Predicting poor response to anti-osteoporosis therapy: a machine learning model integrating clinical and novel biomarker data
10.3389/fmed.2026.1786209 · doi-reference
Bone mineral density response prediction following osteoporosis treatment using machine learning to aid personalized therapy
10.1038/s41598-021-93152-5 · doi-reference
Evaluating and enhancing large language models' performance in domain-specific medicine: development and usability study with DocOA
10.2196/58158 · doi-reference
Multiple large language models versus clinical guidelines for postmenopausal osteoporosis: a comparative study of ChatGPT-3.5, ChatGPT-4.0, ChatGPT-4o, Google Gemini, Google Gemini Advanced, and Microsoft Copilot
10.1007/s11657-025-01587-4 · doi-reference
Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: a 2-D numerical study
10.1016/j.compbiomed.2019.103457 · doi-reference
Artificial intelligence for osteoporosis diagnosis, risk prediction and therapy: current advances, clinical challenges, and future perspectives
10.2147/cia.s607232 · doi-reference
Deep learning-assisted radiomics for predicting thoracolumbar osteoporotic vertebral fractures
10.2147/cia.s600030 · doi-reference
An explainable machine learning approach to predict fragility fractures and the identification of important features
10.1038/s41598-026-49494-z · doi-reference
Sequence-specific radiomics for diagnosis of spinal bone loss
10.3389/fendo.2026.1823826 · doi-reference
Exploring osteoporosis risk in breast cancer patients after comprehensive treatment via explainable artificial intelligence algorithms
10.1016/j.suronc.2026.102455 · doi-reference
Machine learning-driven prediction of low BMD in postmenopausal women using cytokine, RANKL/OPG, and oxidative stress biomarker signatures: an exploratory study
10.3390/biomedicines14061358 · doi-reference