MeSH_retrospective_dataset

This repository includes the implementation of the Retrospective Beyond MeSH (RetroBM) method for the development of large-scale retrospective datasets for fine-grained semantic indexing, as described in the study[1]. This is a part of the work "Deep Beyond MeSH (DBM)", which is a Large-scale investigation of weakly-supervised deep learning for the fine-grained semantic indexing of biomedical literature. The implementation of the Deep Beyond MeSH (DBM) method is available here.

In particular, this repository includes:

1. The dataset development: The dataset creation based on a retrospective scenario, using the concept occurrence in the title or abstract of an article as heuristic.
2. The enhancement of the dataset: The enhancement is achieved by combining a number of heuristics, beyond the concept occurrence.

Reference

[1]: Nentidis, A., Chatzopoulos, T., Krithara, A., Tsoumakas, G., & Paliouras, G. (2023). Large-scale fine-grained semantic indexing of biomedical literature based on weakly-supervised deep learning (arXiv preprint: 2301.09350v1). https://arxiv.org/pdf/2301.09350.pdf