Published on in Vol 8, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18953, first published .
The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

Authors of this article:

Renzo Rivera Zavala 1, 2 Author Orcid Image ;   Paloma Martinez 1 Author Orcid Image

Journals

  1. Chopard D, Treder M, Corcoran P, Ahmed N, Johnson C, Busse M, Spasic I. Text Mining of Adverse Events in Clinical Trials: Deep Learning Approach. JMIR Medical Informatics 2021;9(12):e28632 View
  2. Rivera-Zavala R, Martínez P. Analyzing transfer learning impact in biomedical cross-lingual named entity recognition and normalization. BMC Bioinformatics 2021;22(S1) View
  3. Stortenbeker I, Salm L, olde Hartman T, Stommel W, Das E, van Dulmen S. Coding linguistic elements in clinical interactions: a step-by-step guide for analyzing communication form. BMC Medical Research Methodology 2022;22(1) View
  4. Solarte Pabón O, Montenegro O, Torrente M, Rodríguez González A, Provencio M, Menasalvas E. Negation and uncertainty detection in clinical texts written in Spanish: a deep learning-based approach. PeerJ Computer Science 2022;8:e913 View
  5. Weng K, Liu C, Chen C. Deep Learning Approach for Negation and Speculation Detection for Automated Important Finding Flagging and Extraction in Radiology Report: Internal Validation and Technique Comparison Study. JMIR Medical Informatics 2023;11:e46348 View
  6. Abbasi N, Lacson R, Kapoor N, Licaros A, Guenette J, Burk K, Hammer M, Desai S, Eappen S, Saini S, Khorasani R. Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging. American Journal of Roentgenology 2023;221(3):377 View
  7. Argüello-González G, Aquino-Esperanza J, Salvador D, Bretón-Romero R, Del Río-Bermudez C, Tello J, Menke S. Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network. BMC Medical Informatics and Decision Making 2023;23(1) View
  8. Perez N, Cuadros M, Rigau G. Negation and speculation processing: A study on cue-scope labelling and assertion classification in Spanish clinical text. Artificial Intelligence in Medicine 2023;145:102682 View