Leveraging machine learning to identify acute myeloid leukemia patients and their chemotherapy regimens in an administrative database.

Lusha Cao Yuan-Shung V HuangChao WuKelly GetzTamara P Miller Jenny RuizBrian T FisherAlix E SeifRichard AplencYimei Li

Published in: Pediatric blood & cancer (2023)

A carefully designed ML model can accurately identify pediatric AML patients and their chemotherapy courses from administrative databases. This approach may be generalizable to other diseases and databases.

Keyphrases

acute myeloid leukemia
end stage renal disease
machine learning
newly diagnosed
ejection fraction
chronic kidney disease
prognostic factors
big data
emergency department
artificial intelligence
patient reported