@inproceedings{a03ea11868364fd38ff7bdd62662940b,
title = "A dashboard for latent class trajectory modeling: Application in rheumatoid arthritis",
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.",
keywords = "Medical Informatics Applications, Precision Medicine, Rheumatoid Arthritis",
author = "Beatrice Amico and Arianna Dagliati and Darren Plant and Anne Barton and Niels Peek and Nophar Geifman",
note = "Publisher Copyright: {\textcopyright} 2019 International Medical Informatics Association (IMIA) and IOS Press.; 17th World Congress on Medical and Health Informatics, MEDINFO 2019 ; Conference date: 25-08-2019 Through 30-08-2019",
year = "2019",
month = aug,
day = "21",
doi = "10.3233/SHTI190356",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "911--915",
editor = "Brigitte Seroussi and Lucila Ohno-Machado and Lucila Ohno-Machado and Brigitte Seroussi",
booktitle = "MEDINFO 2019",
address = "Netherlands",
}