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Hong-Jun Yoon
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2020 – today
- 2024
- [j16]Alina Peluso
, Ioana Danciu, Hong-Jun Yoon, Jamaludin Mohd-Yusof
Deep learning uncertainty quantification for clinical text classification. J. Biomed. Informatics 149: 104576 (2024) - [j15]Hong-Jun Yoon
Development of message passing-based graph convolutional networks for classifying cancer pathology reports. BMC Medical Informatics Decis. Mak. 24-S(5): 262 (2024) - [i2]Hong-Jun Yoon, Chris Keum, Alexander Witkowski, Joanna Ludzik, Tracy Petrie, Heidi A. Hanson, Sancy A. Leachman:
Enhancing Diagnosis through AI-driven Analysis of Reflectance Confocal Microscopy. CoRR abs/2404.16080 (2024) - 2023
- [c32]Huanhuan Zhao
Enhancing Text Classification Models with Generative AI-aided Data Augmentation. AITest 2023: 138-145 - [c31]Adam Saunders, Sajal Dash, Aristeidis Tsaris, Hong-Jun Yoon:
A comparison of histopathology imaging comprehension algorithms based on multiple instance learning. Digital and Computational Pathology 2023 - [c30]Aristeidis Tsaris
Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks. PASC 2023: 2:1-2:11 - [i1]Xiao Wang, Isaac Lyngaas, Aristeidis Tsaris, Peng Chen, Sajal Dash, Mayanka Chandra Shekar, Tao Luo, Hong-Jun Yoon, Mohamed Wahib, John Gounley
Ultra-Long Sequence Distributed Transformer. CoRR abs/2311.02382 (2023) - 2022
- [j14]Kevin De Angeli, Shang Gao, Ioana Danciu, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer A. Doherty, Stephen M. Schwartz, Charles Wiggins, Mark Damesyn, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi, Hong-Jun Yoon:
Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types. J. Biomed. Informatics 125: 103957 (2022) - [j13]Andrew E. Blanchard
A Keyword-Enhanced Approach to Handle Class Imbalance in Clinical Text Classification. IEEE J. Biomed. Health Informatics 26(6): 2796-2803 (2022) - [c29]Folami Alamudun, Jacob D. Hinkle, Sajal Dash
Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification. IEEE Big Data 2022: 3393-3397 - [c28]Sajal Dash
A Scalable Pipeline for Gigapixel Whole Slide Imaging Analysis on Leadership Class HPC Systems. IPDPS Workshops 2022: 1266-1274 - [c27]Priscilla Cho, Sajal Dash
Image transformers for classifying acute lymphoblastic leukemia. Computer-Aided Diagnosis 2022 - 2021
- [j12]Kevin De Angeli, Shang Gao
Deep active learning for classifying cancer pathology reports. BMC Bioinform. 22(1): 113 (2021) - [j11]Mohammed M. Alawad
Privacy-Preserving Deep Learning NLP Models for Cancer Registries. IEEE Trans. Emerg. Top. Comput. 9(3): 1219-1230 (2021) - [j10]Shang Gao
Limitations of Transformers on Clinical Text Classification. IEEE J. Biomed. Health Informatics 25(9): 3596-3607 (2021) - [c26]Jeremy Logan
Creating a Tools Ecosystem for Cross-Discipline Environmental Data Reuse. IEEE BigData 2021: 3705-3708 - [c25]Priscilla Cho, Hong-Jun Yoon:
Evaluation of U-net-based image segmentation model to digital mammography. Image Processing 2021 - [c24]Srikanth B. Yoginath
Secure Collaborative Environment for Seamless Sharing of Scientific Knowledge. SMC 2021: 139-156 - 2020
- [j9]Mohammed M. Alawad, Shang Gao, John X. Qiu, Hong-Jun Yoon, James Blair Christian, Lynne Penberthy, Brent J. Mumphrey, Xiao-Cheng Wu, Linda Coyle, Georgia D. Tourassi:
Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks. J. Am. Medical Informatics Assoc. 27(1): 89-98 (2020) - [j8]Hong-Jun Yoon, Hilda B. Klasky, John P. Gounley
Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports. J. Biomed. Informatics 110: 103564 (2020) - [c23]Hong-Jun Yoon
Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles. Poly/DMAH@VLDB 2020: 87-99 - [c22]Peter F. Michael, Hong-Jun Yoon:
Survey of image denoising methods for medical image classification. Computer-Aided Diagnosis 2020
2010 – 2019
- 2019
- [j7]Shang Gao, John X. Qiu, Mohammed M. Alawad, Jacob D. Hinkle
Classifying cancer pathology reports with hierarchical self-attention networks. Artif. Intell. Medicine 101 (2019) - [c21]Mohammed M. Alawad, Shang Gao, John X. Qiu, Noah Schaefferkoetter, Jacob D. Hinkle
Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports. BHI 2019: 1-4 - [c20]Abhishek Kumar Dubey, Hong-Jun Yoon, Georgia D. Tourassi:
Inverse Regression for Extraction of Tumor Site from Cancer Pathology Reports. BHI 2019: 1-4 - [c19]John X. Qiu, Shang Gao, Mohammed M. Alawad, Noah Schaefferkoetter, Folami Alamudun, Hong-Jun Yoon, Xiao-Cheng Wu, Georgia D. Tourassi:
Semi-Supervised Information Extraction for Cancer Pathology Reports. BHI 2019: 1-4 - [c18]Hong-Jun Yoon, John Gounley
Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC. BHI 2019: 1-4 - [c17]Hong-Jun Yoon, John Gounley
Information Extraction from Cancer Pathology Reports with Graph Convolution Networks for Natural Language Texts. IEEE BigData 2019: 4561-4564 - [c16]Hong-Jun Yoon, John X. Qiu, James Blair Christian, Jacob D. Hinkle, Folami Alamudun
Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks. INNSBDDL 2019: 89-98 - [c15]Devanshu Agrawal, Hong-Jun Yoon, Georgia D. Tourassi, Jacob D. Hinkle
Computer-aided detection using non-convolutional neural network Gaussian processes. Computer-Aided Diagnosis 2019: 109503N - 2018
- [j6]John X. Qiu, Hong-Jun Yoon, Kshitij Srivastava, Thomas P. Watson, James Blair Christian, Arvind Ramanathan, Xiao-Cheng Wu, Paul A. Fearn, Georgia D. Tourassi:
Scalable deep text comprehension for Cancer surveillance on high-performance computing. BMC Bioinform. 19-S(18): 99-110 (2018) - [j5]Shang Gao, Michael T. Young, John X. Qiu, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Georgia D. Tourassi, Arvind Ramanathan:
Hierarchical attention networks for information extraction from cancer pathology reports. J. Am. Medical Informatics Assoc. 25(3): 321-330 (2018) - [j4]John X. Qiu, Hong-Jun Yoon
Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports. IEEE J. Biomed. Health Informatics 22(1): 244-251 (2018) - [c14]Mohammed M. Alawad
Coarse-to-fine multi-task training of convolutional neural networks for automated information extraction from cancer pathology reports. BHI 2018: 218-221 - [c13]Hong-Jun Yoon, Sarah Robinson, James Blair Christian, John X. Qiu, Georgia D. Tourassi:
Filter pruning of Convolutional Neural Networks for text classification: A case study of cancer pathology report comprehension. BHI 2018: 345-348 - [c12]Hong-Jun Yoon, Arvind Ramanathan, Folami Alamudun
Deep radiogenomics for predicting clinical phenotypes in invasive breast cancer. IWBI 2018: 107181H - 2017
- [c11]Hong-Jun Yoon, Larry Roberts, Georgia D. Tourassi:
Automated histologic grading from free-text pathology reports using graph-of-words features and machine learning. BHI 2017: 369-372 - [c10]Mohammed M. Alawad
Energy efficient stochastic-based deep spiking neural networks for sparse datasets. IEEE BigData 2017: 311-318 - [c9]Folami T. Alamudun, Tracy Hammond
Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology. HCI (14) 2017: 123-138 - 2016
- [j3]Georgia D. Tourassi, Hong-Jun Yoon, Songhua Xu, Xuesong Han:
The utility of web mining for epidemiological research: studying the association between parity and cancer risk. J. Am. Medical Informatics Assoc. 23(3): 588-595 (2016) - [j2]Georgia D. Tourassi
A novel web informatics approach for automated surveillance of cancer mortality trends. J. Biomed. Informatics 61: 110-118 (2016) - [c8]Hong-Jun Yoon, Georgia D. Tourassi
Investigating the association between sociodemographic factors and lung cancer risk using cyber informatics. BHI 2016: 557-560 - [c7]Hong-Jun Yoon, Songhua Xu, Georgia D. Tourassi
Predicting lung cancer incidence from air pollution exposures using shapelet-based time series analysis. BHI 2016: 565-568 - [c6]Hong-Jun Yoon, Arvind Ramanathan, Georgia D. Tourassi:
Multi-task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports. INNS Conference on Big Data 2016: 195-204 - [c5]Folami Alamudun
Shapelet analysis of pupil dilation for modeling visuo-cognitive behavior in screening mammography. Image Perception, Observer Performance, and Technology Assessment 2016: 97870M - 2015
- [c4]Hong-Jun Yoon, Georgia D. Tourassi
Residential Mobility and Lung Cancer Risk: Data-Driven Exploration Using Internet Sources. SBP 2015: 464-469 - 2014
- [j1]Songhua Xu, Hong-Jun Yoon, Georgia D. Tourassi
A user-oriented web crawler for selectively acquiring online content in e-health research. Bioinform. 30(1): 104-114 (2014) - [c3]Yang Liu, Songhua Xu, Hong-Jun Yoon, Georgia D. Tourassi:
Extracting Patient Demographics and Personal Medical Information from Online Health Forums. AMIA 2014 - 2011
- [c2]Hong-Jun Yoon, Ching-Chung Li, Christhunesa Christudass, Robert Veltri, Jonathan I. Epstein, Zhen Zhang:
Cardinal Multiridgelet-based Prostate Cancer Histological Image Classification for Gleason Grading. BIBM 2011: 315-320
2000 – 2009
- 2006
- [c1]Dev P. Chakraborty, Hong-Jun Yoon:
A maximum likelihood method for estimating the parameters of a search model. ISBI 2006: 1304-1307
Coauthor Index
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