Most of current text mining efforts are focused on the extraction of information from the main body of scientific articles. However, a significant part of the information presented in the literature is shown in figures and tables. For example, the key characteristics of clinical trials may be presented in a table. Processing such elements are often limited to associated textual captions, and the data presented in tables (and figures) are typically ignored. The aim of this PhD project is to explore table mining in the biomedical literature and develop a system to support the curation of relevant information from tables.
- Milosevic, N., Gregson, C., Hernandez, R. Nenadic, G. A framework for information extraction from tables in biomedical literature International Journal on Document Analysis and Recognition (2019). https://doi.org/10.1007/s10032-019-00317-0
- Milosevic,N; Gregson, C; Hernandez, R; Nenadic, G. (2016, June). Disentangling the Structure of Tables in Scientific Literature. In Natural Language Processing and Information Systems: 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, Salford, UK, June 22-24, 2016, Proceedings (Vol. 9612, p. 162). Springer. https://link.springer.com/chapter/10.1007/978-3-319-41754-7_14
- Milosevic, N., Gregson, C., Hernandez, R., & Nenadic, G. (2016). Extracting patient data from tables in clinical literature: Case study on extraction of BMI, weight and number of patients.. In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies ISBN 978-989-758-170-0, pages 223-228. DOI: https://doi.org/10.5220/0005660102230228
- Milosevic, N., Gregson, C., Hernandez, R., & Nenadic, G. Hybrid methodology for information extraction from tables in the biomedical literature. In Proceedings of the Belgrade Bioinformatics Conference (BelBi2016)
- Milosevic, N. (2016). Marvin: Semantic annotation using multiple knowledge sources. arXiv preprint arXiv:1602.00515.