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July 9, 2024International Journal of Medical InformaticsOpen Access

Assessing domain adaptation in adverse drug event extraction on real-world breast cancer records

Gabriel Herman Bernardim Andrade Tomohiro Nishiyama Takako Fujimaki Shuntaro Yada Shoko Wakamiya Mari Takagi Mizuki Kato Isao Miyashiro Eiji Aramaki

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Abstract

Adverse Drug Events (ADE) are key information present in unstructured portions of Electronic Health Records. These pose a significant challenge in healthcare, ranging from mild discomfort to severe complications, and can impact patient safety and treatment outcomes.

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Cite This Study

Andrade et al. (2024) studied this question.

synapsesocial.com/papers/68e60e3db6db6435875a0e7f https://doi.org/10.1016/j.ijmedinf.2024.105539

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1MultiADE: A Multi-domain Benchmark for Adverse Drug Event Extraction2024
2Development of a text mining algorithm for identifying adverse drug reactions in electronic health records2024 · 10 citations
3Evaluating the Robustness of Adverse Drug Event Classification Models Using Templates2024
4Evaluation of adverse drug reactions in cancer-related settings using diverse real-world dataHuman Clinical Trial · 2026
5Leveraging Unstructured Data in Electronic Health Records to Detect Adverse Events from Pediatric Drug Use: A Scoping Review2025 · 2 citations

More related papers

Free Text Analysis: Identification of adverse drug events in clinical notes2024
PersADE: a database of personalized adverse drug events and their underlying molecular mechanisms2025
Mining Real-World Big Data to Characterize Adverse Drug Reaction Quantitatively: Mixed Methods Study2024

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