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Development of an adverse outcome pathway for radiation-induced microcephaly via expert consultation and machine learning.

Thomas JayletRoel QuintensMohamed Abderrafi BenotmaneJukka LuukkonenIgnacia Braga TanakaChrystelle IbanezChristelle DurandMagdalini SachanaOmid AzimzadehChristelle Adam-GuillerminKnut Erik TollefsenOlivier LaurentKarine AudouzeOlivier Armant
Published in: International journal of radiation biology (2022)
The expert consultation led to the identification of crucial biological events for the progression of microcephaly upon exposure to IR, and highlighted current knowledge gaps. The machine learning approach was successfully used to screen the existing knowledge and helped to rapidly screen the body of evidence and in particular the epidemiological data. This systematic review approach also ensured that the analysis was sufficiently comprehensive to identify the most relevant data and facilitate rapid and consistent AOP development. We anticipate that as machine learning approaches become more user-friendly through easy-to-use web interface, this would allow AOP development to become more efficient and less time consuming.
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