Machine Learning Predicts 30-Day Outcome among Acute Myeloid Leukemia Patients: A Single-Center, Retrospective, Cohort Study

Machine Learning Predicts 30-Day Outcome among Acute Myeloid Leukemia Patients: A Single-Center, Retrospective, Cohort Study

Acute myeloid leukemia (AML) is a clinical emergency requiring treatment and results in high 30-day (D30) mortality. In this study, the prediction of D30 survival was studied using a machine learning (ML) method. The total cohort consisted of 1700 survivors and 130 non-survivors at D30. Eight clinic...

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Bibliographic Details
Main Authors: Howon Lee, Jay Ho Han, Jae Kwon Kim, Jaeeun Yoo, Jae-Ho Yoon, Byung Sik Cho, Hee-Je Kim, Jihyang Lim, Dong Wook Jekarl, Yonggoo Kim
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Journal of Clinical Medicine
Subjects:
acute myeloid leukemia
early death
machine learning
decision tree
classification
hemorrhage
Online Access:https://www.mdpi.com/2077-0383/12/18/5940

Internet

https://www.mdpi.com/2077-0383/12/18/5940

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