Comparing neural models for nested and overlapping biomedical event detection

Autor: Kurt Espinosa, Panagiotis Georgiadis, Fenia Christopoulou, Meizhi Ju, Makoto Miwa, Sophia Ananiadou

Publikováno v: BMC Bioinformatics, Vol 23, Iss 1, Pp 1-22 (2022)

Abstract Background Nested and overlapping events are particularly frequent and informative structures in biomedical event extraction. However, state-of-the-art neural models either neglect those structures during learning or use syntactic features a

Externí odkaz: https://doaj.org/article/7c01e99abf474f518e1044c96d4bf46e

A Creative Industry Image Generation Dataset Based on Captions

Autor: Yuejia, Xiang, Chuanhao, Lv, Qingdazhu, Liu, Xiaocui, Yang, Bo, Liu, Meizhi, Ju

Most image generation methods are difficult to precisely control the properties of the generated images, such as structure, scale, shape, etc., which limits its large-scale application in creative industries such as conceptual design and graphic desi

Externí odkaz: http://arxiv.org/abs/2211.09035

Leveraging Multiple Types of Domain Knowledge for Safe and Effective Drug Recommendation

Autor: Jialun Wu, Buyue Qian, Yang Li, Zeyu Gao, Meizhi Ju, Yifan Yang, Yefeng Zheng, Tieliang Gong, Chen Li, Xianli Zhang

Publikováno v: Proceedings of the 31st ACM International Conference on Information & Knowledge Management.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3e18732b5ffe10deaea75c817b1f84aa
https://doi.org/10.1145/3511808.3557380

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

Autor: Elisabetta Iavarone, Meizhi Ju, Christian O'Reilly, Sophia Ananiadou, Matthew Shardlow, John McNaught, Maolin Li

Publikováno v: Neuroinformatics
Shardlow, M, Ju, M, Li, M, O’Reilly, C, Iavarone, E, McNaught, J & Ananiadou, S 2019, ' A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience ', Neuroinformatics, vol. 17, no. 3, pp. 391-406 . https://doi.org/10.1007/s12021-018-9404-y, https://doi.org/10.1007/s12021-018-9404-y

The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e70bbd15bed5350adb7d26b8681b828
http://europepmc.org/articles/PMC6594987

Annotating and detecting phenotypic information for chronic obstructive pulmonary disease

Autor: Sophia Ananiadou, Paul Thompson, Andrea D. Short, Nawar Diar Bakerly, Loukia Tsaprouni, Georgios V. Gkoutos, Meizhi Ju

Publikováno v: JAMIA Open
Ju, M, Short, A, Thompson, P, Diar Bakerly, N, Gkoutos, G, Tsaprouni, L & Ananiadou, S 2019, ' Annotating and Detecting Phenotypic Information for Chronic Obstructive Pulmonary Disease ', Journal of the American Medical Informatics Association . https://doi.org/10.1093/jamiaopen/ooz009

Objectives Chronic obstructive pulmonary disease (COPD) phenotypes cover a range of lung abnormalities. To allow text mining methods to identify pertinent and potentially complex information about these phenotypes from textual data, we have developed

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d6afc5bf5c6aab0776b54501d19f19e
https://pubmed.ncbi.nlm.nih.gov/31984360