ShennongAlpha: an AI-driven sharing and collaboration platform for intelligent curation, acquisition, and translation of natural medicinal material knowledge
arxiv(2023)
摘要
Natural Medicinal Materials (NMMs) have a long history of global clinical
applications and a wealth of records and knowledge. Although NMMs are a major
source for drug discovery and clinical application, the utilization and sharing
of NMM knowledge face crucial challenges, including the standardized
description of critical information, efficient curation and acquisition, and
language barriers. To address these, we developed ShennongAlpha, an AI-driven
sharing and collaboration platform for intelligent knowledge curation,
acquisition, and translation. For standardized knowledge curation, the platform
introduced a Systematic Nomenclature to enable accurate differentiation and
identification of NMMs. More than fourteen thousand Chinese NMMs have been
curated into the platform along with their knowledge. Furthermore, the platform
pioneered chat-based knowledge acquisition, standardized machine translation,
and collaborative knowledge updating. Together, our study represents the first
major advance in leveraging AI to empower NMM knowledge sharing, which not only
marks a novel application of AI for Science, but also will significantly
benefit the global biomedical, pharmaceutical, physician, and patient
communities.
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