Published on in Vol 9, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24678, first published .
Extracting Drug Names and Associated Attributes From Discharge Summaries: Text Mining Study

Extracting Drug Names and Associated Attributes From Discharge Summaries: Text Mining Study

Extracting Drug Names and Associated Attributes From Discharge Summaries: Text Mining Study

Journals

  1. Ma X, Lu Y, Lu Y, Jiang M. SIMEON: Prediction of Chemical-protein Interaction via Stacked Bi-GRU-normalization Network and External Biomedical Knowledge. Current Bioinformatics 2022;17(9):848 View
  2. Dong T, Zhu M, Li R, Wang X. Challenges of Utilizing Medical Big Data in Reproductive Health Research. Frontiers in Reproductive Health 2022;4 View
  3. Fernandes M, Valizadeh N, Alabsi H, Quadri S, Tesh R, Bucklin A, Sun H, Jain A, Brenner L, Ye E, Ge W, Collens S, Lin S, Das S, Robbins G, Zafar S, Mukerji S, Brandon Westover M. Classification of neurologic outcomes from medical notes using natural language processing. Expert Systems with Applications 2023;214:119171 View
  4. Modi S, Kasmiran K, Mohd Sharef N, Sharum M. Extracting adverse drug events from clinical Notes: A systematic review of approaches used. Journal of Biomedical Informatics 2024;151:104603 View
  5. Majdik Z, Graham S, Shiva Edward J, Rodriguez S, Karnes M, Jensen J, Barbour J, Rousseau J. Sample Size Considerations for Fine-Tuning Large Language Models for Named Entity Recognition Tasks: Methodological Study. JMIR AI 2024;3:e52095 View
  6. Jolly A, Pandey V, Singh I, Sharma N. Exploring Biomedical Named Entity Recognition via SciSpaCy and BioBERT Models. The Open Biomedical Engineering Journal 2024;18(1) View
  7. Alasmari A, Zhou L. Quality Measurement of Consumer Health Questions: Content and Language Perspectives (Preprint). Journal of Medical Internet Research 2023 View

Books/Policy Documents

  1. Guan M. Machine Learning and Deep Learning in Computational Toxicology. View