Estimation of the Exposure-Response Relation between Benzene and Acute Myeloid Leukemia by Combining Epidemiologic, Human Biomarker, and Animal Data.

Bernice ScholtenLützen PortengenAnjoeka PronkRob StierumGeorge S DownwardJelle VlaanderenRoel C H Vermeulen

Published in: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology (2022)

By describing a framework for data integration and explicitly describing the necessary data harmonization steps, we hope to enable risk assessors to better understand the advantages and assumptions underlying a data integration approach.See related commentary by Keil, p. 695.

Keyphrases

electronic health record
acute myeloid leukemia
big data
endothelial cells
machine learning
data analysis
acute lymphoblastic leukemia