- Agrawal, Rakesh, Tomasz Imielinski, and Arun Swami. Mining association rules between sets of items in large databases. Acm sigmod record. Vol. 22. No. 2. ACM, 1993.
- Antony B. Holmes, Alexander Hawson, Feng Liu, Carol Friedman, Hossein Khiabanian, and Raul Rabadan. Discovering disease associations by integrating electronic clinical data and medical literature. PloS one, 6(6):e21132+, 2011.
- Duque, A., Martinez-Romo, J., Araujo, L.: Extracción no supervisada de relaciones entre medicamentos y efectos adversos. Procesamiento del Lenguaje Natural 55: 83-90 (2015).
- Andrés Duque Fernandez, Juan Martinez-Romo, Lourdes Araujo: Can multilinguality improve Biomedical Word Sense Disambiguation? Journal of Biomedical Informatics 64: 320-332 (2016)
- Martinez-Romo, J., Araujo, J., Borge-Holthoefer, J., Arenas, A., Capitán, J.A. y Cuesta, J.A. 2011. Disentangling categorical relationships through a graph of co-occurrences. Phys. Rev. E, 84:046108.
- Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781.
- Rashid, Mahmood A., Md Tamjidul Hoque, and Abdul Sattar. "Association rules mining based clinical observations." arXiv preprint arXiv:1401.2571 (2014).
- Sánchez-de-Madariaga R, Muñoz A, Cáceres J, et al. ccML, a new markup language to improve ISO/EN 13606-based Electronic Health Record extracts practical edition. J Am Med Inform Assoc. 2013; 20:298-304.
- Sánchez-de-Madariaga, R., Fernández-del-Castillo, J.R. 2009. The bootstrapping of the Yarowsky algorithm in real corpora. Information Processing & Management 45 2009 55-69.
- Stilou, S., Bamidis, P. D., Maglaveras, N., & Pappas, C. (2001). Mining association rules from clinical databases: an intelligent diagnostic process in healthcare. Studies in health technology and informatics, (2), 1399-1403.
- Wu, Y., Xu, J., Zhang, Y., & Xu, H. (2015). Clinical abbreviation disambiguation using neural word embeddings. ACL-IJCNLP 2015, 171.
Referencias
Noticias
NLP-IR Group - UNED