Unsupervised clustering analysis of data from an online community to identify lupus patient profiles with regards to treatment preferences.
Damien TestaNoémie Jourde-ChicheJulien ManciniPasquale VarrialeLise RadoszyckiLaurent ChichePublished in: Lupus (2021)
Different profiles of lupus patients were identified according to their drug preferences. These clusters could help physicians tailor their therapeutic proposals to take into account individual patient preferences, which could have a positive impact on treatment acceptance and then adherence. The study highlights the value of data acquired directly from patient communities.
Keyphrases
- case report
- systemic lupus erythematosus
- primary care
- electronic health record
- ejection fraction
- disease activity
- mental health
- big data
- newly diagnosed
- decision making
- emergency department
- type diabetes
- rheumatoid arthritis
- prognostic factors
- skeletal muscle
- weight loss
- artificial intelligence
- replacement therapy
- patient reported