| Literature DB >> 31438056 |
Beatrice Amico1, Arianna Dagliati2,3, Darren Plant4, Anne Barton4,5, Niels Peek2,5, Nophar Geifman2.
Abstract
A key trend in current medical research is a shift from a one-size-fit-all to precision treatment strategies, where the focus is on identifying narrow subgroups of the population that would benefit from a given intervention. Precision medicine will greatly benefit from accessible tools that clinicians can use to identify such subgroups, and to generate novel inferences about the patient population they are treating. We present a novel dashboard app that enables clinician users to explore patient subgroups with varying longitudinal treatment response, using latent class mixed modeling. The dashboard was developed in R Shiny. We present results of our approach applied to an observational study of patients with moderate to severe rheumatoid arthritis (RA) on first-line biologic treatment.Entities:
Keywords: Medical Informatics Applications; Precision Medicine; Rheumatoid Arthritis
Mesh:
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Year: 2019 PMID: 31438056 DOI: 10.3233/SHTI190356
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630