The combination of supervised and unsupervised learning based risk stratification and phenotyping in pulmonary arterial hypertension-a long-term retrospective multicenter trial.
Thomas SonnweberPiotr TymoszukRegina Steringer-MascherbauerElisabeth SigmundStephanie Porod-SchneiderbauerLisa KohlbacherIgor TheurlIrene LangGünter WeissJudith Löffler-RaggPublished in: BMC pulmonary medicine (2023)
Supervised and unsupervised learning algorithms such as Elastic Net regression and medoid clustering are powerful tools for automated mortality risk prediction and clinical phenotyping in PAH.
Keyphrases
- machine learning
- pulmonary arterial hypertension
- high throughput
- pulmonary artery
- pulmonary hypertension
- cross sectional
- deep learning
- clinical trial
- study protocol
- single cell
- cardiovascular events
- phase iii
- phase ii
- risk factors
- randomized controlled trial
- rna seq
- cardiovascular disease
- double blind
- coronary artery
- open label
- type diabetes
- placebo controlled