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Artificial Intelligence in Toxicology: The Good, the Bad, and the Overfit

Title: Artificial Intelligence in Toxicology: The Good, the Bad, and the Overfit
Authors: Joseph L. Bundy
Publication Year: 2024
Collection: United States Environmental Protection Agency: Figshare
Subject Terms: Toxicology (incl. clinical toxicology); High Throughput Transcriptomics; Molecular Initiating Events; Machine Learning; New Approach Methods (Alternatives to Animal Testing)
Description: Presentation to HEEDS EDC-North Carolina Working Group Fourth Annual Scientific Meeting Search for CCTE records in EPA’s Science Inventory by typing in the title at this link. https://cfpub.epa.gov/si/si_public_search_results.cfm?advSearch=true&showCriteria=2&keyword=CCTE&TIMSType=&TIMSSubTypeID=&epaNumber=&ombCat=Any&dateBeginPublishedPresented=07/01/2017&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&DEID=&personName=&personID=&role=Any&journalName=&journalID=&publisherName=&publisherID=&sortBy=pubDate&count=25
Document Type: conference object
Language: unknown
Relation: https://figshare.com/articles/presentation/Artificial_Intelligence_in_Toxicology_The_Good_the_Bad_and_the_Overfit/25564251
DOI: 10.23645/epacomptox.25564251.v1
Availability: https://doi.org/10.23645/epacomptox.25564251.v1; https://figshare.com/articles/presentation/Artificial_Intelligence_in_Toxicology_The_Good_the_Bad_and_the_Overfit/25564251
Rights: CC0
Accession Number: edsbas.3FD0F6C1
Database: BASE