Machine learning can predict disease manifestations and outcomes in lymphangioleiomyomatosis.

Saisakul ChernbumroongJanice JohnsonNishant GuptaSuzanne Miller Francis X McCormack Jonathan M Garibaldi Simon R Johnson

Published in: The European respiratory journal (2021)

Machine learning has identified clinically relevant clusters associated with complications and outcome. Assigning individuals to clusters could improve decision making and prognostic information for patients.

Keyphrases

machine learning
end stage renal disease
decision making
ejection fraction
newly diagnosed
artificial intelligence
chronic kidney disease
peritoneal dialysis
big data
healthcare
type diabetes
skeletal muscle
health information
patient reported outcomes
patient reported
weight loss
social media
insulin resistance