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Identifying Chemical-Disease Relationship in Biomedical Text Using a Multiple Kernel Learning-Boosting Method
- Source :
- Studies in health technology and informatics. 245
- Publication Year :
- 2018
-
Abstract
- 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.
- Subjects :
- Machine Learning
Artificial Intelligence
Data Mining
Humans
Disease
Algorithms
Subjects
Details
- ISSN :
- 18798365
- Volume :
- 245
- Database :
- OpenAIRE
- Journal :
- Studies in health technology and informatics
- Accession number :
- edsair.pmid..........27c0487d602b1bf53b4c728e18e3794c