Ricardo Henao
Assistant Professor in Biostatistics and Bioinformatics
Appointments and Affiliations
- Assistant Professor in Biostatistics and Bioinformatics
- Assistant Professor in the Department of Electrical and Computer Engineering
- Member of Duke Center for Applied Genomics and Precision Medicine
- Member of the Duke Clinical Research Institute
Contact Information
- Office Location: 140 Science Drive, Durham, NC 27710
- Office Phone: (919) 668-0647
- Email Address: ricardo.henao@duke.edu
Education
- Ph.D. Technical University of Denmark (Denmark), 2011
Courses Taught
- COMPSCI 394: Research Independent Study
- ECE 391: Projects in Electrical and Computer Engineering
- ECE 899: Special Readings in Electrical Engineering
- EGR 190: Special Topics in Engineering
- POE 190: Practice Oriented Education
In the News
- New Collaborative Seed Grant Program Gives Eight Awards (Mar 16, 2016)
Representative Publications
- Lydon, EC; Henao, R; Burke, TW; Aydin, M; Nicholson, BP; Glickman, SW; Fowler, VG; Quackenbush, EB; Cairns, CB; Kingsmore, SF; Jaehne, AK; Rivers, EP; Langley, RJ; Petzold, E; Ko, ER; McClain, MT; Ginsburg, GS; Woods, CW; Tsalik, EL, Validation of a host response test to distinguish bacterial and viral respiratory infection., Ebiomedicine, vol 48 (2019), pp. 453-461 [10.1016/j.ebiom.2019.09.040] [abs].
- Engelhard, MM; Oliver, JA; Henao, R; Hallyburton, M; Carin, LE; Conklin, C; McClernon, FJ, Identifying Smoking Environments From Images of Daily Life With Deep Learning., Jama Network Open, vol 2 no. 8 (2019) [10.1001/jamanetworkopen.2019.7939] [abs].
- Benitez, M; Tian, J; Kelly, M; Selvakumaran, V; Phelan, M; Mazurowski, M; Lo, JY; Rubin, GD; Henao, R, Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports, Progress in Biomedical Optics and Imaging Proceedings of Spie, vol 10950 (2019) [10.1117/12.2512886] [abs].
- Han, S; Tian, J; Kelly, M; Selvakumaran, V; Henao, R; Rubin, GD; Lo, JY, Classifying abnormalities in computed tomography radiology reports with rule-based and natural language processing models, Progress in Biomedical Optics and Imaging Proceedings of Spie, vol 10950 (2019) [10.1117/12.2513577] [abs].
- Liu, Y; Fu, W; Selvakumaran, V; Phelan, M; Segars, WP; Samei, E; Mazurowski, M; Lo, JY; Rubin, GD; Henao, R, Deep learning of 3D computed tomography (CT) images for organ segmentation using 2D multi-channel SegNet model, Progress in Biomedical Optics and Imaging Proceedings of Spie, vol 10954 (2019) [10.1117/12.2512887] [abs].