Identifying Chemical-Disease Relationship in Biomedical Text Using a Multiple Kernel Learning-Boosting Method
Sun, Y.; Zhang, Y.; Li, J.
Studies in Health Technology and Informatics 245: 1288
2017
ISSN/ISBN: 1879-8365 PMID: 29295373 Document Number: 693596
Chemical-induced disease relations (CID) are crucial in various biomedical tasks. In the CID task of Biocreative V, no classifiers with multiple kernels have been developed. In this study, a multiple kernel learning-boosting (MKLB) method is proposed. Different kernel functions according to different types of features were constucted and boosted, each of which were learned with multiple kernels. Our multiple kernel learning-boosting (MKLB) method achieved a F1 score of 0.5068 without incorporating knowledge bases.