AI Medical Compendium Journal:
Annals of the rheumatic diseases

Showing 1 to 10 of 19 articles

An interpretable machine learning approach for detecting psoriatic arthritis in a UK primary care psoriasis cohort using electronic health records from the Clinical Practice Research Datalink.

Annals of the rheumatic diseases
OBJECTIVES: Develop an interpretable machine learning model to detect patients with newly diagnosed psoriatic arthritis (PsA) in a cohort of psoriasis patients and identify important clinical indicators of PsA in primary care.

Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data.

Annals of the rheumatic diseases
OBJECTIVES: Primary knee osteoarthritis (KOA) is a heterogeneous disease with clinical and molecular contributors. Biofluids contain microRNAs and metabolites that can be measured by omic technologies. Multimodal deep learning is adept at uncovering ...

Performance analysis of a deep-learning algorithm to detect the presence of inflammation in MRI of sacroiliac joints in patients with axial spondyloarthritis.

Annals of the rheumatic diseases
OBJECTIVES: To assess the ability of a previously trained deep-learning algorithm to identify the presence of inflammation on MRI of sacroiliac joints (SIJ) in a large external validation set of patients with axial spondyloarthritis (axSpA).

Assessing the performance of AI chatbots in answering patients' common questions about low back pain.

Annals of the rheumatic diseases
OBJECTIVES: The aim of this study was to assess the accuracy and readability of the answers generated by large language model (LLM)-chatbots to common patient questions about low back pain (LBP).

Predicting rapid progression in knee osteoarthritis: a novel and interpretable automated machine learning approach, with specific focus on young patients and early disease.

Annals of the rheumatic diseases
OBJECTIVES: To facilitate the stratification of patients with osteoarthritis (OA) for new treatment development and clinical trial recruitment, we created an automated machine learning (autoML) tool predicting the rapid progression of knee OA over a ...

From real-world electronic health record data to real-world results using artificial intelligence.

Annals of the rheumatic diseases
With the worldwide digitalisation of medical records, electronic health records (EHRs) have become an increasingly important source of real-world data (RWD). RWD can complement traditional study designs because it captures almost the complete variety...

Nothing about us without us: involving patient collaborators for machine learning applications in rheumatology.

Annals of the rheumatic diseases
Novel machine learning methods open the door to advances in rheumatology through application to complex, high-dimensional data, otherwise difficult to analyse. Results from such efforts could provide better classification of disease, decision support...

Machine learning predicts stem cell transplant response in severe scleroderma.

Annals of the rheumatic diseases
OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT...