Published on in Vol 20, No 6 (2018): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10281, first published .
A Deep Learning Method to Automatically Identify Reports of Scientifically Rigorous Clinical Research from the Biomedical Literature: Comparative Analytic Study

A Deep Learning Method to Automatically Identify Reports of Scientifically Rigorous Clinical Research from the Biomedical Literature: Comparative Analytic Study

A Deep Learning Method to Automatically Identify Reports of Scientifically Rigorous Clinical Research from the Biomedical Literature: Comparative Analytic Study

Journals

  1. Toğaçar M, Ergen B, Cömert Z, Özyurt F. A Deep Feature Learning Model for Pneumonia Detection Applying a Combination of mRMR Feature Selection and Machine Learning Models. IRBM 2020;41(4):212 View
  2. Michelson M, Reuter K. The significant cost of systematic reviews and meta-analyses: A call for greater involvement of machine learning to assess the promise of clinical trials. Contemporary Clinical Trials Communications 2019;16:100443 View
  3. Milliken L, Motomarry S, Kulkarni A. ARtPM: Article Retrieval for Precision Medicine. Journal of Biomedical Informatics 2019;95:103224 View
  4. Varghese A, Agyeman-Badu G, Cawley M. Deep learning in automated text classification: a case study using toxicological abstracts. Environment Systems and Decisions 2020;40(4):465 View
  5. Afzal M, Park B, Hussain M, Lee S. Deep Learning Based Biomedical Literature Classification Using Criteria of Scientific Rigor. Electronics 2020;9(8):1253 View
  6. Li J, Bu Y, Lu S, Pang H, Luo C, Liu Y, Qian L. Development of a Deep Learning–Based Model for Diagnosing Breast Nodules With Ultrasound. Journal of Ultrasound in Medicine 2021;40(3):513 View
  7. Afzal M, Hussain M, Malik K, Lee S. Impact of Automatic Query Generation and Quality Recognition Using Deep Learning to Curate Evidence From Biomedical Literature: Empirical Study. JMIR Medical Informatics 2019;7(4):e13430 View
  8. Carvallo A, Parra D, Lobel H, Soto A. Automatic document screening of medical literature using word and text embeddings in an active learning setting. Scientometrics 2020;125(3):3047 View
  9. Bian J, Abdelrahman S, Shi J, Del Fiol G. Automatic identification of recent high impact clinical articles in PubMed to support clinical decision making using time-agnostic features. Journal of Biomedical Informatics 2019;89:1 View
  10. Tobore I, Li J, Yuhang L, Al-Handarish Y, Kandwal A, Nie Z, Wang L. Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations. JMIR mHealth and uHealth 2019;7(8):e11966 View
  11. Afzal M, Alam F, Malik K, Malik G. Clinical Context–Aware Biomedical Text Summarization Using Deep Neural Network: Model Development and Validation. Journal of Medical Internet Research 2020;22(10):e19810 View
  12. Ambalavanan A, Devarakonda M. Using the contextual language model BERT for multi-criteria classification of scientific articles. Journal of Biomedical Informatics 2020;112:103578 View
  13. Renganathan V. Overview of Deep Learning Models in Biomedical Domain with the Help of R Statistical Software. Serbian Journal of Experimental and Clinical Research 2018;0(0) View
  14. Abdelkader W, Navarro T, Parrish R, Cotoi C, Germini F, Iorio A, Haynes B, Lokker C. Machine Learning Approaches to Retrieve High-Quality, Clinically Relevant, Evidence from the Biomedical Literature: A Systematic Review (Preprint). JMIR Medical Informatics 2021 View

Books/Policy Documents

  1. Hersh W. Information Retrieval: A Biomedical and Health Perspective. View
  2. Jeba Priya S, Joshua Jaistein S, Naveen Sundar G, Raja Sundrapandiyanleebanon T. Smart Computing Techniques and Applications. View