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
- single cell
- phase ii
- study protocol
- phase iii
- rna seq
- cardiovascular events
- cardiovascular disease
- coronary artery
- double blind
- type diabetes
- polycyclic aromatic hydrocarbons
- placebo controlled