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PreprintCited by 3Biomedical Text Mining and OntologiesBioinformatics and Genomic NetworksMisinformation and Its Impacts

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Challenging the Machinery of Generative AI with Fact-Checking: Ontology-Driven Biological Graphs for Verifying Human Disease-Gene Links

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Hamed, Ahmed Abdeen, Crimi, Alessandro, Lee, Byung Suk, Misiak, Magdalena M.·2024·SSRN Electronic Journal
DOI 10.2139/ssrn.4888506
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Citations

Cites

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Research works printed but not linked: 42

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Metadata

Authors
Hamed, A. A., Crimi, A., Lee, B. S., & Misiak, M. M.
Affiliations
  • Binghamton University (US)
  • AGH University of Krakow (PL)
  • University of Vermont (US)
  • Howard University (US)
Corresponding author
Hamed, Ahmed Abdeen
ORCID
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2024
ISSN
1556-5068 (ISSN-L)
DOI
10.2139/ssrn.4888506
OpenAlex
W4400476807
Cited by
3
References
3
Citations by year
2026: 1 · 2025: 1 · 2024: 1
Type
posted content
Language
en
Open access
Locations
SSRN Electronic Journal (acceptedVersion)
Topics
  • Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
Keywords
ChatGPT, biological networks, PubMed abstracts, protein-protein interaction network, gene regulatory networks, IntAct

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CoChat. (2026). Citation check: Challenging the Machinery of Generative AI with Fact-Checking: Ontology-Driven Biological Graphs for Verifying Human Disease-Gene Links. https://app.cochat.ai/papers/10.2139/ssrn.4888506
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Hamed, A. A., Crimi, A., Lee, B. S., & Misiak, M. M. (2024). Challenging the Machinery of Generative AI with Fact-Checking: Ontology-Driven Biological Graphs for Verifying Human Disease-Gene Links. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4888506