Papers by Ikeda Masami
BENNERD: A Neural Named Entity Linking System for COVID-19 (2020.emnlp-demos)
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| Challenge: | a biomedical entity linking system is available for COVID-19 research. |
| Approach: | They propose a biomedical entity linking system that detects named enti- ties in text and links them to the UMLS knowledge base. |
| Outcome: | The proposed system detects named enti- ties in text and links them to the unified medical language system (UMS) knowledge base entries. |
Disease Network Constructor: a Pathway Extraction and Visualization (2023.acl-demo)
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Mohammad Golam Sohrab, Khoa Duong, Goran Topić, Masami Ikeda, Nozomi Nagano, Yayoi Natsume-Kitatani, Masakata Kuroda, Mari Itoh, Hiroya Takamura
| Challenge: | In the human body, various substances (entities) such as proteins and compounds interact and regulate each other, forming huge pathway networks. |
| Approach: | They present a system that extracts and visualizes a disease network derived through regulation events found in scientific articles on idiopathic pulmonary fibrosis. |
| Outcome: | The proposed system extracts and visualizes a disease network from biomedical articles on idiopathic pulmonary fibrosis (IPF) it includes two-dimensional (2D) and 3D visualizations of the constructed disease network. |
BiomedCurator: Data Curation for Biomedical Literature (2022.aacl-demo)
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Mohammad Golam Sohrab, Khoa N.A. Duong, Ikeda Masami, Goran Topić, Yayoi Natsume-Kitatani, Masakata Kuroda, Mari Nogami Itoh, Hiroya Takamura
| Challenge: | BiomedCurator uses state-of-the-art natural language processing techniques to extract structured data from scientific articles. |
| Approach: | They propose a web application that extracts structured data from PubMed and ClinicalTrials.gov . the application uses a combination of natural language processing techniques and a pattern-based extraction approach . |
| Outcome: | The proposed system extracts the structured data from PubMed and ClinicalTrials.gov datasets. |