Hong-Jun Yoon, Ph.D.
Affiliations: | 2011 | University of Pittsburgh, Pittsburgh, PA, United States |
Area:
Electronics and Electrical Engineering, RadiologyGoogle:
"Hong-Jun Yoon"Parents
Sign in to add mentor| Hu Li | grad student | 2011 | University of Pittsburgh | |
| (Multiridgelets for texture analysis.) | ||||
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Publications
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| Yoon HJ, Klasky HB, Gounley JP, et al. (2020) Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports. Journal of Biomedical Informatics. 103564 |
| Gao S, Qiu JX, Alawad M, et al. (2019) Classifying cancer pathology reports with hierarchical self-attention networks. Artificial Intelligence in Medicine. 101: 101726 |
| Qiu JX, Yoon HJ, Srivastava K, et al. (2018) Scalable deep text comprehension for Cancer surveillance on high-performance computing. Bmc Bioinformatics. 19: 488 |
| Gao S, Young MT, Qiu JX, et al. (2017) Hierarchical attention networks for information extraction from cancer pathology reports. Journal of the American Medical Informatics Association : Jamia |
| Qiu J, Yoon HJ, Fearn PA, et al. (2017) Deep Learning for Automated Extraction of Primary Sites from Cancer Pathology Reports. Ieee Journal of Biomedical and Health Informatics |
| Alamudun F, Yoon H, Hammond T, et al. (2016) Shapelet analysis of pupil dilation for modeling visuo-cognitive behavior in screening mammography Proceedings of Spie. 9787 |
| Yoon HJ, Carmichael TR, Tourassi G. (2014) Gaze as a biometric Progress in Biomedical Optics and Imaging - Proceedings of Spie. 9037 |
| Chakraborty DP, Yoon HJ, Mello-Thoms C. (2012) Application of threshold-bias independent analysis to eye-tracking and FROC data. Academic Radiology. 19: 1474-83 |
| Zanca F, Hillis SL, Claus F, et al. (2012) Correlation of free-response and receiver-operating-characteristic area-under-the-curve estimates: results from independently conducted FROC∕ROC studies in mammography. Medical Physics. 39: 5917-29 |
| Veltri RW, Christudass C, Epstein JI, et al. (2012) Abstract 4061: Computer-assisted Gleason grading of prostate cancer: Two novel approaches using nuclear shape and texture feature to classify pathologic Gleason grade patterns 3 and 4 Cancer Research. 72: 4061-4061 |