Identification of PsA phenotypes with machine learning analytics using data from two phase III clinical trials of guselkumab in a bio-naïve population of patients with PsA

Identification of PsA phenotypes with machine learning analytics using data from two phase III clinical trials of guselkumab in a bio-naïve population of patients with PsA

Objectives Psoriatic arthritis (PsA) phenotypes are typically defined by their clinical components, which may not reflect patients’ overlapping symptoms. This post hoc analysis aimed to identify hypothesis-free PsA phenotype clusters using machine learning to analyse data from the phase III DISCOVER...

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Bibliografische gegevens
Hoofdauteurs: Julio Ramírez, Pascal Richette, Alen Zabotti, Sarah Ohrndorf, Elke Theander, Marijn Vis, William Tillett, May Shawi, Wim Noël, Marlies Neuhold, Michel van Speybroeck, Miriam Zimmermann, Alexa Kollmeier
Formaat: Artikel
Taal:English
Gepubliceerd in: BMJ Publishing Group 2023-03-01
Reeks:RMD Open
Online toegang:https://rmdopen.bmj.com/content/9/1/e002934.full

Internet

https://rmdopen.bmj.com/content/9/1/e002934.full

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