ACADSTAFF UGM
| Title | : | Comparison of Machine Learning and Deep Learning model for Medical Subject Headings Indexation |
| Author | : |
Dr. Lukman Heryawan, S.T., M.T. (1) ARIF FARHAN BUKHORI (2) |
| Date | : | 27 2023 |
| Keyword | : | Medical subject headings, Logistic regression, LSTM, Machine learning, Deep learning,Automatic MeSH indexing Medical subject headings, Logistic regression, LSTM, Machine learning, Deep learning,Automatic MeSH indexing |
| Abstract | : | MeSH stands for Medical Subject Heading. MeSH is a thorough mastery for cataloging books and articles in the biomedical literature. MeSH works as a dictionary that facilitates searching and retrieving information in the biomedical realm. Currently, a human indexer manually indexes articles and books in biomedical literature using the MeSH vocabulary. The problem with using a human indexer is that the indexation process takes a long time and is expensive. Therefore, the indexation developed is automated, which is developed in this study using MeSH vocabulary with predictors based on machine learning and supervised deep learning. The study found that the F1-Score of the deep learning indexation model was superior compared to the machine learning used as the baseline model in predicting the indexation. |
| Group of Knowledge | : | |
| Level | : | Internasional |
| Status | : |
Published
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