Opportunities and challenges in applying AI to evolutionary morphology

He, Y., Mulqueeney, J.M., Watt, E.C. orcid.org/0000-0003-0214-7105 et al. (19 more authors) (2024) Opportunities and challenges in applying AI to evolutionary morphology. Integrative Organismal Biology, 6 (1). obae036. ISSN 2517-4843

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Item Type: Article
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© TheAuthor(s) 2024. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords: Biological Sciences; Evolutionary Biology; Data Science; Machine Learning and Artificial Intelligence; Networking and Information Technology R&D (NITRD); Bioengineering; Generic health relevance
Dates:
  • Published: 23 September 2024
  • Published (online): 23 September 2024
  • Accepted: 20 September 2024
  • Submitted: 22 February 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 28 Oct 2024 15:18
Last Modified: 28 Oct 2024 15:18
Status: Published
Publisher: Oxford University Press (OUP)
Refereed: Yes
Identification Number: 10.1093/iob/obae036
Open Archives Initiative ID (OAI ID):

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