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

Theme Issue 2020:National NLP Clinical Challenges/Open Health Natural Language Processing 2019 Challenge Selected Papers (17) Machine Learning (1501) Natural Language Processing (706)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22982, first published .
Extracting Family History of Patients From Clinical Narratives: Exploring an End-to-End Solution With Deep Learning Models

Extracting Family History of Patients From Clinical Narratives: Exploring an End-to-End Solution With Deep Learning Models

Extracting Family History of Patients From Clinical Narratives: Exploring an End-to-End Solution With Deep Learning Models

Authors of this article:

Xi Yang1, 2 Author Orcid Image ;   Hansi Zhang1 Author Orcid Image ;   Xing He1 Author Orcid Image ;   Jiang Bian1, 2 Author Orcid Image ;   Yonghui Wu1, 2 Author Orcid Image
Article Authors Cited by (19) Tweetations (5) Metrics

Journals

  1. Yu Z, Yang X, Sweeting G, Ma Y, Stolte S, Fang R, Wu Y. Identify diabetic retinopathy-related clinical concepts and their attributes using transformer-based natural language processing methods. BMC Medical Informatics and Decision Making 2022;22(S3) View
  2. Kilroy D, Healy G, Caton S. Using Machine Learning to Improve Lead Times in the Identification of Emerging Customer Needs. IEEE Access 2022;10:37774 View
  3. Mithun S, Jha A, Sherkhane U, Jaiswar V, Purandare N, Dekker A, Puts S, Bermejo I, Rangarajan V, Zegers C, Wee L. Clinical Concept-Based Radiology Reports Classification Pipeline for Lung Carcinoma. Journal of Digital Imaging 2023;36(3):812 View
  4. Dedhia P, Chen K, Song Y, LaRose E, Imbus J, Peissig P, Mendonca E, Schneider D. Ambiguous and Incomplete: Natural Language Processing Reveals Problematic Reporting Styles in Thyroid Ultrasound Reports. Methods of Information in Medicine 2022;61(01/02):011 View
  5. Yang X, Chen A, PourNejatian N, Shin H, Smith K, Parisien C, Compas C, Martin C, Costa A, Flores M, Zhang Y, Magoc T, Harle C, Lipori G, Mitchell D, Hogan W, Shenkman E, Bian J, Wu Y. A large language model for electronic health records. npj Digital Medicine 2022;5(1) View
  6. Chiavi D, Haag C, Chan A, Kamm C, Sieber C, Stanikić M, Rodgers S, Pot C, Kesselring J, Salmen A, Rapold I, Calabrese P, Manjaly Z, Gobbi C, Zecca C, Walther S, Stegmayer K, Hoepner R, Puhan M, von Wyl V. The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing. JMIR Medical Informatics 2022;10(11):e37945 View
  7. Landolsi M, Romdhane L, Hlaoua L. Medical Named Entity Recognition using Surrounding Sequences Matching. Procedia Computer Science 2022;207:674 View
  8. Bose P, Srinivasan S, Sleeman W, Palta J, Kapoor R, Ghosh P. A Survey on Recent Named Entity Recognition and Relationship Extraction Techniques on Clinical Texts. Applied Sciences 2021;11(18):8319 View
  9. Panaite V, Devendorf A, Finch D, Bouayad L, Luther S, Schultz S. The Value of Extracting Clinician-Recorded Affect for Advancing Clinical Research on Depression: Proof-of-Concept Study Applying Natural Language Processing to Electronic Health Records. JMIR Formative Research 2022;6(5):e34436 View
  10. Landolsi M, Hlaoua L, Ben Romdhane L. Information extraction from electronic medical documents: state of the art and future research directions. Knowledge and Information Systems 2023;65(2):463 View
  11. Shi J, Morgan K, Bradshaw R, Jung S, Kohlmann W, Kaphingst K, Kawamoto K, Fiol G. Identifying Patients Who Meet Criteria for Genetic Testing of Hereditary Cancers Based on Structured and Unstructured Family Health History Data in the Electronic Health Record: Natural Language Processing Approach. JMIR Medical Informatics 2022;10(8):e37842 View
  12. Landolsi M, Hlaoua L, Romdhane L. Extracting and structuring information from the electronic medical text: state of the art and trendy directions. Multimedia Tools and Applications 2023;83(7):21229 View
  13. Mithun S, Jha A, Sherkhane U, Jaiswar V, Purandare N, Rangarajan V, Dekker A, Puts S, Bermejo I, Wee L. Development and validation of deep learning and BERT models for classification of lung cancer radiology reports. Informatics in Medicine Unlocked 2023;40:101294 View
  14. Kozik R, Mazurczyk W, Cabaj K, Pawlicka A, Pawlicki M, Choraś M. Deep Learning for Combating Misinformation in Multicategorical Text Contents. Sensors 2023;23(24):9666 View
  15. García-Barragán Á, González Calatayud A, Solarte-Pabón O, Provencio M, Menasalvas E, Robles V. GPT for medical entity recognition in Spanish. Multimedia Tools and Applications 2024 View
  16. Yang S, Yang X, Lyu T, Huang J, Chen A, He X, Braithwaite D, Mehta H, Wu Y, Guo Y, Bian J. Extracting Pulmonary Nodules and Nodule Characteristics from Radiology Reports of Lung Cancer Screening Patients Using Transformer Models. Journal of Healthcare Informatics Research 2024;8(3):463 View

Books/Policy Documents

  1. Avasthi S, Sanwal T, Tripathi S, Tyagi M. Mining Biomedical Text, Images and Visual Features for Information Retrieval. View