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Knowledge-enhanced Artificial Intelligence in Drug Discovery (KAIDD)

  • Qingpeng Zhang*
  • , Jiannan Yang
  • *Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Artificial Intelligence (AI) in drug discovery is a rapidly evolving field that combines computational methods with biological knowledge and applications. Traditionally, the process of developing a new drug has been time-consuming and expensive, spanning several years and costing billions of dollars. The emergence of AI technologies offers the potential to significantly reduce both the timeline and cost involved in this critical endeavour. However, it is crucial to acknowledge that AI applications in pharmacy and drug discovery require a high degree of interpretability and transparency. The integration of domain knowledge into AI models becomes paramount to ensure the reliability and trustworthiness of the generated results. In light of these considerations, we propose a workshop on "Knowledge-enhanced Artificial Intelligence in Drug Discovery (KAIDD)." This workshop aims to explore the profound impact of incorporating various knowledge databases into the development of explainable AI models for drug discovery. Participants will have the opportunity to delve into cutting-edge research, methodologies, and practical applications that leverage the fusion of AI techniques with domain-specific knowledge. Authors of accepted papers will have the opportunity to submit extended versions of their work for a full-paper review process and potential publication in Philosophical Transactions of the Royal Society B. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Original languageEnglish
Title of host publicationCIKM '23
Subtitle of host publicationProceedings of the 32nd ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages5308-5310
Number of pages3
ISBN (Print)979-8-4007-0124-5
DOIs
Publication statusPublished - Oct 2023
Externally publishedYes
Event32nd ACM International Conference on Information and Knowledge Management (CIKM 2023) - University of Birmingham and Eastside Rooms, Birmingham, United Kingdom
Duration: 21 Oct 2023 → 25 Oct 2023
https://uobevents.eventsair.com/cikm2023/
https://uobevents.eventsair.com/cikm2023/accepted-papers
https://dl.acm.org/doi/proceedings/10.1145/3583780

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference32nd ACM International Conference on Information and Knowledge Management (CIKM 2023)
Abbreviated titleCIKM ’23
PlaceUnited Kingdom
CityBirmingham
Period21/10/23 → 25/10/23
Internet address

Research Keywords

  • Artificial intelligence
  • Drug discovery
  • Explainable deep learning model
  • Knowledge-enhanced model

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