This paper is in the following e-collection/theme issue:

Natural Language Processing (706) Clinical Informatics (1050) New Methods (963) Speech and Phonetics in Verbal Protocols (Think Aloud, Recall, and Explanation Tasks) (93)

Published on in Vol 3, No 2 (2015): April-June

Benchmarking Clinical Speech Recognition and Information Extraction: New Data, Methods, and Evaluations

Benchmarking Clinical Speech Recognition and Information Extraction: New Data, Methods, and Evaluations

Benchmarking Clinical Speech Recognition and Information Extraction: New Data, Methods, and Evaluations

Authors of this article:

Hanna Suominen1, 2, 3, 4 Author Orcid Image ;   Liyuan Zhou1, 2 Author Orcid Image ;   Leif Hanlen1, 2, 3 Author Orcid Image ;   Gabriela Ferraro1, 2 Author Orcid Image
Article Authors Cited by (26) Tweetations (2) Metrics

Journals

  1. Dong X, Chowdhury S, Qian L, Li X, Guan Y, Yang J, Yu Q, Galstyan A. Deep learning for named entity recognition on Chinese electronic medical records: Combining deep transfer learning with multitask bi-directional LSTM RNN. PLOS ONE 2019;14(5):e0216046 View
  2. Kaufman D, Sheehan B, Stetson P, Bhatt A, Field A, Patel C, Maisel J. Natural Language Processing–Enabled and Conventional Data Capture Methods for Input to Electronic Health Records: A Comparative Usability Study. JMIR Medical Informatics 2016;4(4):e35 View
  3. Chen Q, Lee K, Yan S, Kim S, Wei C, Lu Z, Kann M. BioConceptVec: Creating and evaluating literature-based biomedical concept embeddings on a large scale. PLOS Computational Biology 2020;16(4):e1007617 View
  4. Rankin D, Black M, Bond R, Wallace J, Mulvenna M, Epelde G. Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing. JMIR Medical Informatics 2020;8(7):e18910 View
  5. Mairittha T, Mairittha N, Inoue S. Evaluating a Spoken Dialogue System for Recording Systems of Nursing Care. Sensors 2019;19(17):3736 View
  6. Mairittha T, Mairittha N, Inoue S. Automatic Labeled Dialogue Generation for Nursing Record Systems. Journal of Personalized Medicine 2020;10(3):62 View
  7. Liu H, Hu Q, He L. Term-Based Personalization for Feature Selection in Clinical Handover Form Auto-Filling. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2019;16(4):1219 View
  8. Velupillai S, Suominen H, Liakata M, Roberts A, Shah A, Morley K, Osborn D, Hayes J, Stewart R, Downs J, Chapman W, Dutta R. Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances. Journal of Biomedical Informatics 2018;88:11 View
  9. Arnold T, Fuller H. An Ergonomic Framework for Researching and Designing Speech Recognition Technologies in Health Care with an Emphasis on Safety. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 2019;8(1):279 View
  10. Zhou L, Suominen H, Gedeon T. Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potentials, Challenges, and Solutions. JMIR Medical Informatics 2019;7(2):e11499 View
  11. Blackley S, Huynh J, Wang L, Korach Z, Zhou L. Speech recognition for clinical documentation from 1990 to 2018: a systematic review. Journal of the American Medical Informatics Association 2019;26(4):324 View
  12. Suominen H, Kelly L, Goeuriot L. Scholarly Influence of the Conference and Labs of the Evaluation Forum eHealth Initiative: Review and Bibliometric Study of the 2012 to 2017 Outcomes. JMIR Research Protocols 2018;7(7):e10961 View
  13. Chowdhury S, Dong X, Qian L, Li X, Guan Y, Yang J, Yu Q. A multitask bi-directional RNN model for named entity recognition on Chinese electronic medical records. BMC Bioinformatics 2018;19(S17) View
  14. Joseph J, Moore Z, Patton D, O'Connor T, Nugent L. The impact of implementing speech recognition technology on the accuracy and efficiency (time to complete) clinical documentation by nurses: A systematic review. Journal of Clinical Nursing 2020;29(13-14):2125 View
  15. Chen J, Lu C, Huang H, Zhu D, Yang Q, Liu J, Huang Y, Deng A, Han X. Cognitive Computing-Based CDSS in Medical Practice. Health Data Science 2021;2021 View
  16. Chen Y. A hidden Markov optimization model for processing and recognition of English speech feature signals. Journal of Intelligent Systems 2022;31(1):716 View
  17. O'Leary L, Erikainen S, Peltonen L, Ahmed W, Thelwall M, O'Connor S. Exploring nurses’ online perspectives and social networks during a global pandemic COVID‐19. Public Health Nursing 2022;39(3):586 View
  18. Mairittha T, Mairittha N, Inoue S. Integrating a spoken dialogue system, nursing records, and activity data collection based on smartphones. Computer Methods and Programs in Biomedicine 2021;210:106364 View
  19. Dinari F, Bahaadinbeigy K, Bassiri S, Mashouf E, Bastaminejad S, Moulaei K. Benefits, barriers, and facilitators of using speech recognition technology in nursing documentation and reporting: A cross‐sectional study. Health Science Reports 2023;6(6) View

Books/Policy Documents

  1. Goeuriot L, Kelly L, Suominen H, Hanlen L, Névéol A, Grouin C, Palotti J, Zuccon G. Experimental IR Meets Multilinguality, Multimodality, and Interaction. View
  2. Kelly L, Goeuriot L, Suominen H, Névéol A, Palotti J, Zuccon G. Experimental IR Meets Multilinguality, Multimodality, and Interaction. View
  3. Suominen H, Kelly L, Goeuriot L. Information Retrieval Evaluation in a Changing World. View
  4. Zhou L, Suominen H. AI 2015: Advances in Artificial Intelligence. View
  5. Buchlak Q, Esmaili N, Bennett C, Farrokhi F. Machine Learning in Clinical Neuroscience. View
  6. Ferizaj D, Neumann S. Human-Computer Interaction. View