Robust Physician Gaze Prediction Using a Deep Learning Approach

Tianyi Tan; Enid Montague; Jacob Furst; Daniela Raicu

doi:10.1109/BIBE50027.2020.00168

Robust Physician Gaze Prediction Using a Deep Learning Approach

Tianyi Tan
, Enid Montague
, Jacob Furst
, Daniela Raicu

DePaul University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020
Publisher	IEEE (Institute of Electrical and Electronics Engineers)
Pages	993-998
Number of pages	6
ISBN (Electronic)	9781728195742
DOIs	https://doi.org/10.1109/BIBE50027.2020.00168
State	Published - Oct 2020
Event	20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020 - Virtual, Cincinnati, United States Duration: Oct 26 2020 → Oct 28 2020

Publication series

Name	Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020

Conference

Conference	20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020
Country/Territory	United States
City	Virtual, Cincinnati
Period	10/26/20 → 10/28/20

ASJC Scopus Subject Areas

Biotechnology
Genetics
Molecular Biology
Artificial Intelligence
Computer Science Applications
Biomedical Engineering
Modeling and Simulation
Health Informatics

Keywords

automatic labeling
deep learning
physician gaze
primary care visits

Access to Document

10.1109/BIBE50027.2020.00168

Cite this

Tan, T., Montague, E., Furst, J., & Raicu, D. (2020). Robust Physician Gaze Prediction Using a Deep Learning Approach. In Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020 (pp. 993-998). Article 9288056 (Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020). IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/BIBE50027.2020.00168

Robust Physician Gaze Prediction Using a Deep Learning Approach. / Tan, Tianyi; Montague, Enid; Furst, Jacob et al.
Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020. IEEE (Institute of Electrical and Electronics Engineers), 2020. p. 993-998 9288056 (Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tan, T, Montague, E, Furst, J & Raicu, D 2020, Robust Physician Gaze Prediction Using a Deep Learning Approach. in Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020., 9288056, Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020, IEEE (Institute of Electrical and Electronics Engineers), pp. 993-998, 20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020, Virtual, Cincinnati, United States, 10/26/20. https://doi.org/10.1109/BIBE50027.2020.00168

Tan T, Montague E, Furst J, Raicu D. Robust Physician Gaze Prediction Using a Deep Learning Approach. In Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020. IEEE (Institute of Electrical and Electronics Engineers). 2020. p. 993-998. 9288056. (Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020). doi: 10.1109/BIBE50027.2020.00168

Tan, Tianyi ; Montague, Enid ; Furst, Jacob et al. / Robust Physician Gaze Prediction Using a Deep Learning Approach. Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020. IEEE (Institute of Electrical and Electronics Engineers), 2020. pp. 993-998 (Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020).

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author = "Tianyi Tan and Enid Montague and Jacob Furst and Daniela Raicu",

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Robust Physician Gaze Prediction Using a Deep Learning Approach

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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