[HTML][HTML] Data integration challenges for machine learning in precision medicine

M Martínez-García, E Hernández-Lemus - Frontiers in medicine, 2022 - frontiersin.org
A main goal of Precision Medicine is that of incorporating and integrating the vast corpora on
different databases about the molecular and environmental origins of disease, into analytic …

Knowledge graphs for the life sciences: Recent developments, challenges and opportunities

J Chen, H Dong, J Hastings, E Jiménez-Ruiz… - arXiv preprint arXiv …, 2023 - arxiv.org
The term life sciences refers to the disciplines that study living organisms and life processes,
and include chemistry, biology, medicine, and a range of other related disciplines. Research …

Understanding geological reports based on knowledge graphs using a deep learning approach

B Wang, L Wu, Z Xie, Q Qiu, Y Zhou, K Ma… - Computers & Geosciences, 2022 - Elsevier
Geological reports aid in understanding exploration by providing valuable information on
rock formation, evolution and the geological environment in which deposits formed …

Comparison of biomedical relationship extraction methods and models for knowledge graph creation

N Milošević, W Thielemann - Journal of Web Semantics, 2023 - Elsevier
Biomedical research is growing at such an exponential pace that scientists, researchers,
and practitioners are no more able to cope with the amount of published literature in the …

Hierarchical representation and deep learning–based method for automatically transforming textual building codes into semantic computable requirements

R Zhang, N El-Gohary - Journal of Computing in Civil Engineering, 2022 - ascelibrary.org
Most of the existing automated compliance checking (ACC) systems are unable to fully
automatically convert building-code requirements, especially requirements that have …

[HTML][HTML] Relation extraction for biological pathway construction using node2vec

M Kim, SH Baek, M Song - BMC bioinformatics, 2018 - Springer
Background Systems biology is an important field for understanding whole biological
mechanisms composed of interactions between biological components. One approach for …

[HTML][HTML] Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical …

Q Chen, J Du, S Kim, WJ Wilbur, Z Lu - BMC medical informatics and …, 2020 - Springer
Background Capturing sentence semantics plays a vital role in a range of text mining
applications. Despite continuous efforts on the development of related datasets and models …

Models and techniques for domain relation extraction: a survey

J Wang, K Yue, L Duan - Journal of Data Science and …, 2023 - ojs.bonviewpress.com
As the significant subtask of information extraction, relation extraction (RE) aims to identify
and classify semantic relations between pairs of entities and is widely adopted as the …

[HTML][HTML] Joint learning-based causal relation extraction from biomedical literature

D Li, P Wu, Y Dong, J Gu, L Qian, G Zhou - Journal of Biomedical …, 2023 - Elsevier
Causal relation extraction of biomedical entities is one of the most complex tasks in
biomedical text mining, which involves two kinds of information: entity relations and entity …

BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language

CT Hoyt, D Domingo-Fernández… - Database, 2018 - academic.oup.com
The rapid accumulation of knowledge in the field of systems and networks biology during
recent years requires complex, but user-friendly and accessible web applications that allow …