Knowledge-enhanced Artificial Intelligence in Drug Discovery (KAIDD)

Knowledge-enhanced Artificial Intelligence in Drug Discovery (KAIDD)

연구 분야: Artificial Intelligence

학회: CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management

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.