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Combined Molecular Fingerprint and Descriptor Features Enable Classical Machine Learning to Match Deep Learning Performance Across the Tox21 Toxicity Panel.

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Title: Combined Molecular Fingerprint and Descriptor Features Enable Classical Machine Learning to Match Deep Learning Performance Across the Tox21 Toxicity Panel.
Authors: Agboola, Oluwaseun E.1,2 (AUTHOR) agboolaoe@abuad.edu.ng, Agboola, Samuel S.3 (AUTHOR), Adegbuyi, Adekunle T.4 (AUTHOR), Ayinla, Zainab A.5 (AUTHOR)
Source: Toxicology Mechanisms & Methods. Jul2026, p1-12. 12p. 7 Illustrations.
Database: Academic Search Ultimate
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Header DbId: asn
DbLabel: Academic Search Ultimate
An: 195269365
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: <searchLink fieldCode="JN" term="%22Toxicology+Mechanisms+%26+Methods%22">Toxicology Mechanisms & Methods</searchLink>. Jul2026, p1-12. 12p. 7 Illustrations.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=195269365
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/15376516.2026.2703006
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 1
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      – TitleFull: Combined Molecular Fingerprint and Descriptor Features Enable Classical Machine Learning to Match Deep Learning Performance Across the Tox21 Toxicity Panel.
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      – PersonEntity:
          Name:
            NameFull: Agboola, Oluwaseun E.
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            NameFull: Agboola, Samuel S.
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            NameFull: Adegbuyi, Adekunle T.
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            NameFull: Ayinla, Zainab A.
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            – D: 11
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
          Identifiers:
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              Value: 15376516
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            – TitleFull: Toxicology Mechanisms & Methods
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