Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome
Journal
EBioMedicine
Journal Volume
37
Pages
91
Date Issued
2018-11
Author(s)
Wang, Yu-Fen
Li, Jeng-Lin
Li, Chi-Cheng
Weng, Pei-Fang
Lin, Chien-Ting
Lee, Chi-Chun
Abstract
Multicolor flow cytometry (MFC) analysis is widely used to identify minimal residual disease (MRD) after treatment for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). However, current manual interpretation suffers from drawbacks of time consuming and interpreter idiosyncrasy. Artificial intelligence (AI), with the expertise in assisting repetitive or complex analysis, represents a potential solution for these drawbacks.
Subjects
Acute myeloid leukemia; Artificial intelligence; Minimal residual disease; Multicolor flow cytometry; Myelodysplastic syndrome
Publisher
ELSEVIER
Type
journal article