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

Natural Language Processing (692)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13331, first published .
Improving the Efficacy of the Data Entry Process for Clinical Research With a Natural Language Processing–Driven Medical Information Extraction System: Quantitative Field Research

Improving the Efficacy of the Data Entry Process for Clinical Research With a Natural Language Processing–Driven Medical Information Extraction System: Quantitative Field Research

Improving the Efficacy of the Data Entry Process for Clinical Research With a Natural Language Processing–Driven Medical Information Extraction System: Quantitative Field Research

Authors of this article:

Jiang Han1, 2 Author Orcid Image ;   Ken Chen3 Author Orcid Image ;   Lei Fang3 Author Orcid Image ;   Shaodian Zhang3, 4 Author Orcid Image ;   Fei Wang3, 5 Author Orcid Image ;   Handong Ma3, 6 Author Orcid Image ;   Liebin Zhao2, 7 Author Orcid Image ;   Shijian Liu1, 2 Author Orcid Image
Article Authors Cited by (15) Tweetations (4) Metrics

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  6. Weissler E, Naumann T, Andersson T, Ranganath R, Elemento O, Luo Y, Freitag D, Benoit J, Hughes M, Khan F, Slater P, Shameer K, Roe M, Hutchison E, Kollins S, Broedl U, Meng Z, Wong J, Curtis L, Huang E, Ghassemi M. The role of machine learning in clinical research: transforming the future of evidence generation. Trials 2021;22(1) View
  7. Ma H, Sheng W, Li J, Hou L, Yang J, Cai J, Xu W, Zhang S. A novel hierarchical machine learning model for hospital-acquired venous thromboembolism risk assessment among multiple-departments. Journal of Biomedical Informatics 2021;122:103892 View
  8. Wang N, Zhang Y, Wang W, Ye Z, Chen H, Hu G, Ouyang D. How can machine learning and multiscale modeling benefit ocular drug development?. Advanced Drug Delivery Reviews 2023;196:114772 View
  9. Lai P, Mohan A, Kim S, Chu J, Lee S, Kafle P, Wang P. Customized Information Extraction and Processing Pipeline for Commercial Invoices. International Journal of Pattern Recognition and Artificial Intelligence 2023;37(09) View
  10. Liu Q, Yahyapour R, Liu H, Hu Y. A novel combining method of dynamic and static web crawler with parallel computing. Multimedia Tools and Applications 2024;83(21):60343 View
  11. Franklin J, Marra C, Abebe K, Butte A, Cook D, Esserman L, Fleisher L, Grossman C, Kass N, Krumholz H, Rowan K, Abernethy A, Abbasi A, Abebe K, Abernethy A, Adam S, Angus D, Ard J, Bender Ignacio R, Berkwits M, Berry S, Bhatt D, Bibbins-Domingo K, Bonow R, Bonten M, Brangman S, Brownstein J, Buntin M, Butte A, Califf R, Campbell M, Cappola A, Chiang A, Cook D, Cummings S, Curfman G, Esserman L, Fleisher L, Franklin J, Gonzalez R, Grossman C, Haddad T, Herbst R, Hernandez A, Holder D, Horn L, Huang G, Huang A, Kass N, Khera R, Koroshetz W, Landray M, Lewis R, Lieu T, Malani P, Martin C, McClellan M, McDermott M, Morain S, Murphy S, Nicholls S, Nicholls S, O'Dwyer P, Patel B, Peterson E, Prindiville S, Ross J, Rowan K, Rubenfeld G, Seymour C, Taylor R, Waldstreicher J, Wang T. Modernizing the Data Infrastructure for Clinical Research to Meet Evolving Demands for Evidence. JAMA 2024;332(16):1378 View

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  1. Khadela A, Popat S, Ajabiya J, Valu D, Savale S, Chavda V. Bioinformatics Tools for Pharmaceutical Drug Product Development. View
  2. Attar S, Degraeuwe E, Walle J, Turner M. Essentials of Translational Pediatric Drug Development. View