Evaluation of Machine Learning Models for Detecting Disambiguation on Medical Abbreviations-Reference-Cited by-同舟云学术

Evaluation of Machine Learning Models for Detecting Disambiguation on Medical Abbreviations

Published:2022-11-22 Issue: Volume: Page:
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Container-title:Proceedings of the 2022 International Conference on Computer, Control, Informatics and Its Applications
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Author:

Yuwana Raden Sandra¹^ORCID,Andini Ruth²^ORCID,Pardede Hilman¹^ORCID,Sulandari Winita³^ORCID,Suryawati Endang¹^ORCID,Ihsan Candra¹^ORCID,Supianto Ahmad Afif¹^ORCID

Affiliation:

1. National Research and Innovation Agency (BRIN), Indonesia

2. Sebelas Maret University, Indonesia

3. Universitas Sebelas Maret, Indonesia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3575882.3575907

Reference22 articles.

1. Skreta , M. , Arbabi , A. , Wang , J. , & Brudno , M. ( 2020 , April). Training without training data: Improving the generalizability of automated medical abbreviation disambiguation . In Machine Learning for Health Workshop (pp. 233-245) . PMLR.. Skreta, M., Arbabi, A., Wang, J., & Brudno, M. (2020, April). Training without training data: Improving the generalizability of automated medical abbreviation disambiguation. In Machine Learning for Health Workshop (pp. 233-245). PMLR..

2. Holper , S. , Barmanray , R. , Colman , B. , Yates , C. J. , Liew , D. , & Smallwood , D. ( 2020 ). Ambiguous medical abbreviation study: challenges and opportunities. Internal medicine journal, 50(9), 1073-1078 .. Holper, S., Barmanray, R., Colman, B., Yates, C. J., Liew, D., & Smallwood, D. (2020). Ambiguous medical abbreviation study: challenges and opportunities. Internal medicine journal, 50(9), 1073-1078..

3. A convolutional route to abbreviation disambiguation in clinical text

4. A sense inventory for clinical abbreviations and acronyms created using clinical notes and medical dictionary resources

5. Zweigenbaum , P. , Deléger , L. , Lavergne , T. , Névéol , A. , & Bodnari , A. ( 2013 ). A Supervised Abbreviation Resolution System for Medical Text . In CLEF (Working Notes). Zweigenbaum, P., Deléger, L., Lavergne, T., Névéol, A., & Bodnari, A. (2013). A Supervised Abbreviation Resolution System for Medical Text. In CLEF (Working Notes).