| 配分額 *注記 |
4,680千円 (直接経費: 3,600千円、間接経費: 1,080千円)
2026年度: 1,300千円 (直接経費: 1,000千円、間接経費: 300千円)
2025年度: 1,430千円 (直接経費: 1,100千円、間接経費: 330千円)
2024年度: 1,950千円 (直接経費: 1,500千円、間接経費: 450千円)
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| 研究開始時の研究の概要 |
We will introduce a knowledge-aware neural disease network (KANDN) that will extract diseases, proteins, genes, compounds that interact and regulate each other as events in scientific articles. We will construct a knowledge-aware transformer-based neural pre-trained language model that represents the context-aware input vector by integrating knowledge. In this implementation, several NLP techniques including neural NER, EL, RE, and EE will be addressed as an end-to-end joint learning approach to generate more precise and accurate KANDN from the biomedical domain to facilitate the end users.
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