Addressing the challenges of reconstructing systematic reviews datasets: a case study and a noisy label filter procedure
Abstract Systematic reviews and meta-analyses typically require significant time and effort. Machine learning models have the potential to enhance screening efficiency in these processes. To effectively evaluate such models, fully labeled datasets—detailing all records screened by humans and their l...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-02-01
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| Series: | Systematic Reviews |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13643-024-02472-w |