Ricardo Henao

Associate Professor in the Department of Electrical and Computer Engineering

Appointments and Affiliations

  • Associate Professor in Biostatistics & Bioinformatics
  • Assistant Professor in the Department of Electrical and Computer Engineering
  • Member of Duke Center for Applied Genomics and Precision Medicine

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

  • ECE 392: Projects in Electrical and Computer Engineering
  • ECE 494: Projects in Electrical and Computer Engineering
  • ECE 891: Internship
  • ECE 899: Special Readings in Electrical Engineering
  • EGR 393: Research Projects in Engineering
  • IDS 793: Independent Study

In the News

Representative Publications

  • Economou-Zavlanos, Nicoleta J., Sophia Bessias, Michael P. Cary, Armando D. Bedoya, Benjamin A. Goldstein, John E. Jelovsek, Cara L. O’Brien, et al. “Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare.” J Am Med Inform Assoc 31, no. 3 (February 16, 2024): 705–13. https://doi.org/10.1093/jamia/ocad221.
  • Hong, Chuan, Molei Liu, Daniel M. Wojdyla, Jimmy Hickey, Michael Pencina, and Ricardo Henao. “Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance.” J Biomed Inform 149 (January 2024): 104532. https://doi.org/10.1016/j.jbi.2023.104532.
  • Assaad, Serge, David Dov, Christine Park, Richard Davis, Shahar Z. Kovalsky, Walter T. Lee, Russel R. Kahmke, et al. “A preliminary study comparing the performance of thyroid molecular tests to a deep learning algorithm in predicting malignancy in indeterminate thyroid fine needle aspiration biopsies.” Thyroid, November 27, 2023. https://doi.org/10.1089/thy.2023.0054.
  • Steinbrink, Julie M., Yiling Liu, Ricardo Henao, Ephraim L. Tsalik, Geoffrey S. Ginsburg, Elizabeth Ramsburg, Christopher W. Woods, and Micah T. McClain. “305. PBMC-Derived Transcriptomic Signatures Accurately Discriminate Between Viral, Bacterial, and Fungal Infections and can be Translated to Real-World Human Infections.” Open Forum Infectious Diseases 10, no. Supplement_2 (November 27, 2023). https://doi.org/10.1093/ofid/ofad500.377.
  • Dow, Eliot R., Hyeon Ki Jeong, Ella Arnon Katz, Cynthia A. Toth, Dong Wang, Terry Lee, David Kuo, et al. “A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography.” JAMA Ophthalmol 141, no. 11 (November 1, 2023): 1052–61. https://doi.org/10.1001/jamaophthalmol.2023.4659.