Published on in Vol 7, No 3 (2019): Jul-Sep
![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](https://asset.jmir.pub/assets/33a0ebcc61e1d3a8cd35257f4ae4b366.png 480w,https://asset.jmir.pub/assets/33a0ebcc61e1d3a8cd35257f4ae4b366.png 960w,https://asset.jmir.pub/assets/33a0ebcc61e1d3a8cd35257f4ae4b366.png 1920w,https://asset.jmir.pub/assets/33a0ebcc61e1d3a8cd35257f4ae4b366.png 2500w)
1 Pediatric Translational Medicine Institute, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
2 School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
3 Synyi Research, Shanghai, China
4 APEX Data and Knowledge Management Lab, Shanghai Jiao Tong University, Shanghai, China
5 Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY, United States
6 Department of computer science, Shanghai Jiao Tong University, Shanghai, China
7 Child Health Advocacy Institute, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
*these authors contributed equally