Published on in Vol 7, No 3 (2019): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14185, first published .
A Real-Time Automated Patient Screening System for Clinical Trials Eligibility in an Emergency Department: Design and Evaluation

A Real-Time Automated Patient Screening System for Clinical Trials Eligibility in an Emergency Department: Design and Evaluation

A Real-Time Automated Patient Screening System for Clinical Trials Eligibility in an Emergency Department: Design and Evaluation

Journals

  1. Chamberlin S, Bedrick S, Cohen A, Wang Y, Wen A, Liu S, Liu H, Hersh W. Evaluation of patient-level retrieval from electronic health record data for a cohort discovery task. JAMIA Open 2020;3(3):395 View
  2. Ni Y, Barzman D, Bachtel A, Griffey M, Osborn A, Sorter M. Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence. International Journal of Medical Informatics 2020;139:104137 View
  3. Stubbs A, Filannino M, Soysal E, Henry S, Uzuner Ö. Cohort selection for clinical trials: n2c2 2018 shared task track 1. Journal of the American Medical Informatics Association 2019;26(11):1163 View
  4. Spasic I, Krzeminski D, Corcoran P, Balinsky A. Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining Approach. JMIR Medical Informatics 2019;7(4):e15980 View
  5. Kirubarajan A, Taher A, Khan S, Masood S. Artificial intelligence in emergency medicine: A scoping review. Journal of the American College of Emergency Physicians Open 2020;1(6):1691 View
  6. Naik H, Palaniappan L, Ashley E, Scott S. Digital Health Applications for Pharmacogenetic Clinical Trials. Genes 2020;11(11):1261 View
  7. Naceanceno K, House S, Asaro P. Shared-Task Worklists Improve Clinical Trial Recruitment Workflow in an Academic Emergency Department. Applied Clinical Informatics 2021;12(02):293 View
  8. von Itzstein M, Hullings M, Mayo H, Beg M, Williams E, Gerber D. Application of Information Technology to Clinical Trial Evaluation and Enrollment. JAMA Oncology 2021;7(10):1559 View
  9. Ni Y, Bachtel A, Nause K, Beal S. Automated detection of substance use information from electronic health records for a pediatric population. Journal of the American Medical Informatics Association 2021;28(10):2116 View
  10. Idnay B, Fang Y, Dreisbach C, Marder K, Weng C, Schnall R. Clinical research staff perceptions on a natural language processing-driven tool for eligibility prescreening: An iterative usability assessment. International Journal of Medical Informatics 2023;171:104985 View
  11. Maheshwari K, Cywinski J, Papay F, Khanna A, Mathur P. Artificial Intelligence for Perioperative Medicine: Perioperative Intelligence. Anesthesia & Analgesia 2023;136(4):637 View
  12. Trenfield S, Awad A, McCoubrey L, Elbadawi M, Goyanes A, Gaisford S, Basit A. Advancing pharmacy and healthcare with virtual digital technologies. Advanced Drug Delivery Reviews 2022;182:114098 View
  13. Munger Clary H, Snively B, Topaloglu U, Duncan P, Kimball J, Alexander H, Brenes G. Patient-reported outcomes via electronic health record portal versus telephone: a pragmatic randomized pilot trial of anxiety or depression symptoms in epilepsy. JAMIA Open 2022;5(4) View
  14. Yu Z, Zhang X, Lv H. Artificial Intelligence Imaging to Observe the Protective Effect of Hydrogen Sulfide on Acute Kidney Injury Caused by Urinary Sepsis. Journal of Sensors 2021;2021:1 View
  15. Kim J, Butler A, Ta C, Sun Y, Maurer M, Weng C. The potential role of EHR data in optimizing eligibility criteria definition for cardiovascular outcome trials. International Journal of Medical Informatics 2021;156:104587 View
  16. Zhuang M, Concannon D, Manley E. A Framework for Evaluating Dashboards in Healthcare. IEEE Transactions on Visualization and Computer Graphics 2022;28(4):1715 View
  17. Jacobsen P, Haddock G, Raphael J, Peak C, Winter R, Berry K. Recruiting and retaining participants in three randomised controlled trials of psychological interventions conducted on acute psychiatric wards: top ten tips for success. BJPsych Open 2022;8(4) View
  18. Bunney G, Sundaram V, Graber-Naidich A, Miller K, Brown I, McCoy A, Freeze B, Berger D, Wright A, Yiadom M. Beyond chest pain: Incremental value of other variables to identify patients for an early ECG. The American Journal of Emergency Medicine 2023;67:70 View
  19. Kanbar L, Wissel B, Ni Y, Pajor N, Glauser T, Pestian J, Dexheimer J. Implementation of Machine Learning Pipelines for Clinical Practice: Development and Validation Study. JMIR Medical Informatics 2022;10(12):e37833 View
  20. Idnay B, Dreisbach C, Weng C, Schnall R. A systematic review on natural language processing systems for eligibility prescreening in clinical research. Journal of the American Medical Informatics Association 2021;29(1):197 View
  21. Maharjan J, Ektefaie Y, Ryan L, Mataraso S, Barnes G, Shokouhi S, Green-Saxena A, Calvert J, Mao Q, Das R. Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm. Frontiers in Neurology 2022;12 View
  22. Branch-Elliman W, Sundermann A, Wiens J, Shenoy E. The future of automated infection detection: Innovation to transform practice (Part III/III). Antimicrobial Stewardship & Healthcare Epidemiology 2023;3(1) View
  23. Meystre S, Heider P, Cates A, Bastian G, Pittman T, Gentilin S, Kelechi T. Piloting an automated clinical trial eligibility surveillance and provider alert system based on artificial intelligence and standard data models. BMC Medical Research Methodology 2023;23(1) View
  24. Stensland K, Sales A, Vedapudi V, Damschroder L, Skolarus T. Exploring implementation outcomes in the clinical trial context: a qualitative study of physician trial stakeholders. Trials 2023;24(1) View
  25. Ismail A, Al-Zoubi T, El Naqa I, Saeed H. The role of artificial intelligence in hastening time to recruitment in clinical trials. BJR|Open 2023;5(1) View
  26. Blasini R, Strantz C, Gulden C, Helfer S, Lidke J, Prokosch H, Sohrabi K, Schneider H. Evaluation of Eligibility Criteria Relevance for the Purpose of IT-Supported Trial Recruitment: Descriptive Quantitative Analysis. JMIR Formative Research 2024;8:e49347 View
  27. Kalankesh L, Monaghesh E. Utilization of EHRs for clinical trials: a systematic review. BMC Medical Research Methodology 2024;24(1) View

Books/Policy Documents

  1. Soomro K, Pimenidis E. Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. View
  2. Gasmi A. Computational Intelligence Techniques for Combating COVID-19. View