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A Dashboard for Latent Class Trajectory Modeling: Application in Rheumatoid Arthritis.

Overview of attention for article published in Studies in health technology and informatics, August 2019
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Article details
Title
A Dashboard for Latent Class Trajectory Modeling: Application in Rheumatoid Arthritis.
Published in
Studies in health technology and informatics, August 2019
DOI 10.3233/shti190356
Pubmed ID
Authors

Beatrice Amico, Arianna Dagliati, Darren Plant, Anne Barton, Niels Peek, Nophar Geifman

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.

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The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Professor 2 18%
Student > Ph. D. Student 2 18%
Researcher 2 18%
Other 1 9%
Student > Postgraduate 1 9%
Other 0 0%
Unknown 3 27%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 4 36%
Biochemistry, Genetics and Molecular Biology 1 9%
Agricultural and Biological Sciences 1 9%
Immunology and Microbiology 1 9%
Engineering 1 9%
Other 0 0%
Unknown 3 27%