ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2016
Using LASSO Regression to Predict Rheumatoid Arthritis Treatment Efficacy.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Machine learning-based study of breath sounds in children with asthma in remission and cough variant asthma.BMC medical informatics and decision making · 2026Observational
- An introduction to machine learning and analysis of its use in rheumatic diseases.Nature reviews. Rheumatology · 2021Review
- The patellofemoral morphology and the normal predicted value of tibial tuberosity-trochlear groove distance in the Chinese population.BMC musculoskeletal disorders · 2021Article
- Non-Invasive Diagnosis for Acute Rejection Using Urinary mRNA Signature Reflecting Allograft Status in Kidney Transplantation.Frontiers in immunology · 2021Article
- Inflammatory arthritis disrupts gut resolution mechanisms, promoting barrier breakdown by Porphyromonas gingivalis.JCI insight · 2019Article
- Assessment of a Deep Learning Model Based on Electronic Health Record Data to Forecast Clinical Outcomes in Patients With Rheumatoid Arthritis.JAMA network open · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Rheumatoid arthritis (RA) accounts for one-fifth of the deaths due to arthritis, the leading cause of disability in the United States. Finding effective treatments for managing arthritis symptoms are a major challenge, since the mechanisms of autoimmune disorders are not fully understood and disease presentation differs for each patient. The American College of Rheumatology clinical guidelines for treatment consider the severity of the disease when deciding treatment, but do not include any prediction of drug efficacy. Using Electronic Health Records and Biomedical Linked Open Data (LOD), we demonstrate a method to classify patient outcomes using LASSO penalized regression. We show how Linked Data improves prediction and provides insight into how drug treatment regimes have different treatment outcome. Applying classifiers like this to decision support in clinical applications could decrease time to successful disease management, lessening a physical and financial burden on patients individually and the healthcare system as a whole.
Identifiers
27570666PMC5001752W2508509771What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.