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Predictive Models for Long Term Survival of AML Patients Treated with Venetoclax and Azacitidine or 7+3 Based on Post Treatment Events and Responses: Retrospective Cohort Study.

Nazmul IslamJamie S ReubenJustin DaleJames W CoatesKaran SapiahFrank R MarksonCraig T JordanClayton A Smith
Published in: JMIR cancer (2024)
Our findings indicate that toxicities, clinical events, and responses evolve differently in patients receiving ven/aza compared with that of 7+3 regimen. ML-based predictive models were shown to be a feasible strategy for CDS in both forms of AML treatment. If validated with larger and more diverse data sets, these findings could offer valuable insights for developing AML-CDS tools that leverage posttreatment clinical data.
Keyphrases
  • acute myeloid leukemia
  • quantum dots
  • electronic health record
  • allogeneic hematopoietic stem cell transplantation
  • machine learning
  • combination therapy
  • deep learning
  • replacement therapy