A maximum likelihood method for estimating the parameters of a search model. - Dev P. Chakraborty; Hong-Jun Yoon (ISBI, 2006)

Cardinal Multiridgelet-based Prostate Cancer Histological Image Classification for Gleason Grading. - Hong-Jun Yoon; Ching-Chung Li; Christhunesa Christudass; Robert Veltri; Jonathan I. Epstein; Zhen Zhang (BIBM, 2011)

Extracting Patient Demographics and Personal Medical Information from Online Health Forums. - Yang Liu 046; Songhua Xu; Hong-Jun Yoon; Georgia D. Tourassi (AMIA, 2014)

A user-oriented web crawler for selectively acquiring online content in e-health research. - Songhua Xu; Hong-Jun Yoon; Georgia D. Tourassi (Bioinform., 2014)

Residential Mobility and Lung Cancer Risk: Data-Driven Exploration Using Internet Sources. - Hong-Jun Yoon; Georgia D. Tourassi; Songhua Xu (SBP, 2015)

Investigating the association between sociodemographic factors and lung cancer risk using cyber informatics. - Hong-Jun Yoon; Georgia D. Tourassi (BHI, 2016)

Predicting lung cancer incidence from air pollution exposures using shapelet-based time series analysis. - Hong-Jun Yoon; Songhua Xu; Georgia D. Tourassi (BHI, 2016)

Multi-task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports. - Hong-Jun Yoon; Arvind Ramanathan; Georgia D. Tourassi (INNS Conference on Big Data, 2016)

Shapelet analysis of pupil dilation for modeling visuo-cognitive behavior in screening mammography. - Folami Alamudun; Hong-Jun Yoon; Tracy Hammond; Kathy Hudson; Garnetta Morin-Ducote; Georgia D. Tourassi (Image Perception, Observer Performance, and Technology Assessment, 2016)

The utility of web mining for epidemiological research: studying the association between parity and cancer risk. - Georgia D. Tourassi; Hong-Jun Yoon; Songhua Xu; Xuesong Han (J. Am. Medical Informatics Assoc., 2016)

A novel web informatics approach for automated surveillance of cancer mortality trends. - Georgia D. Tourassi; Hong-Jun Yoon; Songhua Xu (J. Biomed. Informatics, 2016)

Automated histologic grading from free-text pathology reports using graph-of-words features and machine learning. - Hong-Jun Yoon; Larry Roberts; Georgia D. Tourassi (BHI, 2017)

Energy efficient stochastic-based deep spiking neural networks for sparse datasets. - Mohammed M. Alawad; Hong-Jun Yoon; Georgia D. Tourassi (IEEE BigData, 2017)

Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology. - Folami T. Alamudun; Tracy Hammond; Hong-Jun Yoon; Georgia D. Tourassi (HCI (14), 2017)

Coarse-to-fine multi-task training of convolutional neural networks for automated information extraction from cancer pathology reports. - Mohammed M. Alawad; Hong-Jun Yoon; Georgia D. Tourassi (BHI, 2018)

Filter pruning of Convolutional Neural Networks for text classification: A case study of cancer pathology report comprehension. - Hong-Jun Yoon; Sarah Robinson; James Blair Christian; John X. Qiu; Georgia D. Tourassi (BHI, 2018)

Deep radiogenomics for predicting clinical phenotypes in invasive breast cancer. - Hong-Jun Yoon; Arvind Ramanathan; Folami Alamudun; Georgia D. Tourassi (IWBI, 2018)

Scalable deep text comprehension for Cancer surveillance on high-performance computing. - 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 (BMC Bioinform., 2018)

Hierarchical attention networks for information extraction from cancer pathology reports. - Shang Gao 008; Michael T. Young; John X. Qiu; Hong-Jun Yoon; James Blair Christian; Paul A. Fearn; Georgia D. Tourassi; Arvind Ramanathan (J. Am. Medical Informatics Assoc., 2018)

Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports. - John X. Qiu; Hong-Jun Yoon; Paul A. Fearn; Georgia D. Tourassi (IEEE J. Biomed. Health Informatics, 2018)

Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports. - Mohammed M. Alawad; Shang Gao 008; John X. Qiu; Noah Schaefferkoetter; Jacob D. Hinkle; Hong-Jun Yoon; James Blair Christian; Xiao-Cheng Wu; Eric B. Durbin; Jong Cheol Jeong; Isaac Hands; David Rust; et al. (BHI, 2019)

Inverse Regression for Extraction of Tumor Site from Cancer Pathology Reports. - Abhishek Kumar Dubey; Hong-Jun Yoon; Georgia D. Tourassi (BHI, 2019)

Semi-Supervised Information Extraction for Cancer Pathology Reports. - John X. Qiu; Shang Gao 008; Mohammed M. Alawad; Noah Schaefferkoetter; Folami Alamudun; Hong-Jun Yoon; Xiao-Cheng Wu; Georgia D. Tourassi (BHI, 2019)

Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC. - Hong-Jun Yoon; John Gounley; Shang Gao 008; Mohammed M. Alawad; Arvind Ramanathan; Georgia D. Tourassi (BHI, 2019)

Information Extraction from Cancer Pathology Reports with Graph Convolution Networks for Natural Language Texts. - Hong-Jun Yoon; John Gounley; M. Todd Young; Georgia D. Tourassi (IEEE BigData, 2019)

Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks. - Hong-Jun Yoon; John X. Qiu; James Blair Christian; Jacob D. Hinkle; Folami Alamudun; Georgia D. Tourassi (INNSBDDL, 2019)

Computer-aided detection using non-convolutional neural network Gaussian processes. - Devanshu Agrawal; Hong-Jun Yoon; Georgia D. Tourassi; Jacob D. Hinkle (Computer-Aided Diagnosis, 2019)

Classifying cancer pathology reports with hierarchical self-attention networks. - Shang Gao 008; John X. Qiu; Mohammed M. Alawad; Jacob D. Hinkle; Noah Schaefferkoetter; Hong-Jun Yoon; James Blair Christian; Paul A. Fearn; Lynne Penberthy; Xiao-Cheng Wu; Linda Coyle; Georgia D. Tourassi; et al. (Artif. Intell. Medicine, 2019)

Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles. - Hong-Jun Yoon; Hilda B. Klasky; Eric B. Durbin; Xiao-Cheng Wu; Antoinette Stroup; Jennifer A. Doherty; Linda Coyle; Lynne Penberthy; Christopher B. Stanley; James Blair Christian; Georgia D. Tourassi (Poly/DMAH@VLDB, 2020)

Survey of image denoising methods for medical image classification. - Peter F. Michael; Hong-Jun Yoon (Computer-Aided Diagnosis, 2020)

Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks. - Mohammed M. Alawad; Shang Gao 008; John X. Qiu; Hong-Jun Yoon; James Blair Christian; Lynne Penberthy; Brent J. Mumphrey; Xiao-Cheng Wu; Linda Coyle; Georgia D. Tourassi (J. Am. Medical Informatics Assoc., 2020)

Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports. - Hong-Jun Yoon; Hilda B. Klasky; John P. Gounley; Mohammed M. Alawad; Shang Gao 008; Eric B. Durbin; Xiao-Cheng Wu; Antoinette Stroup; Jennifer A. Doherty; Linda Coyle; Lynne Penberthy; James Blair Christian; et al. (J. Biomed. Informatics, 2020)

Creating a Tools Ecosystem for Cross-Discipline Environmental Data Reuse. - Jeremy Logan; Greeshma A. Agasthya; Heidi A. Hanson; Matthew Wolf; Heechan Lee; Shaheen Dewji; Hong-Jun Yoon; Anuj J. Kapadia (IEEE BigData, 2021)

Evaluation of U-net-based image segmentation model to digital mammography. - Priscilla Cho; Hong-Jun Yoon (Image Processing, 2021)

Secure Collaborative Environment for Seamless Sharing of Scientific Knowledge. - Srikanth B. Yoginath; Mathieu Doucet; Debsindhu Bhowmik; David Heise; Folami Alamudun; Hong-Jun Yoon; Christopher B. Stanley (SMC, 2021)

Deep active learning for classifying cancer pathology reports. - Kevin De Angeli; Shang Gao 008; Mohammed M. Alawad; Hong-Jun Yoon; Noah Schaefferkoetter; Xiao-Cheng Wu; Eric B. Durbin; Jennifer A. Doherty; Antoinette Stroup; Linda Coyle; Lynne Penberthy; Georgia D. Tourassi (BMC Bioinform., 2021)

Privacy-Preserving Deep Learning NLP Models for Cancer Registries. - Mohammed M. Alawad; Hong-Jun Yoon; Shang Gao 008; Brent J. Mumphrey; Xiao-Cheng Wu; Eric B. Durbin; Jong Cheol Jeong; Isaac Hands; David Rust; Linda Coyle; Lynne Penberthy; Georgia D. Tourassi (IEEE Trans. Emerg. Top. Comput., 2021)

Limitations of Transformers on Clinical Text Classification. - Shang Gao 008; Mohammed M. Alawad; M. Todd Young; John Gounley; Noah Schaefferkoetter; Hong-Jun Yoon; Xiao-Cheng Wu; Eric B. Durbin; Jennifer A. Doherty; Antoinette Stroup; Linda Coyle; Georgia D. Tourassi (IEEE J. Biomed. Health Informatics, 2021)

Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification. - Folami Alamudun; Jacob D. Hinkle; Sajal Dash; Benjamín Hernández; Aristeidis Tsaris; Hong-Jun Yoon (IEEE Big Data, 2022)

A Scalable Pipeline for Gigapixel Whole Slide Imaging Analysis on Leadership Class HPC Systems. - Sajal Dash; Benjamín Hernández; Aristeidis Tsaris; Folami T. Alamudun; Hong-Jun Yoon; Feiyi Wang (IPDPS Workshops, 2022)

Image transformers for classifying acute lymphoblastic leukemia. - Priscilla Cho; Sajal Dash; Aristeidis Tsaris; Hong-Jun Yoon (Computer-Aided Diagnosis, 2022)

Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types. - Kevin De Angeli; Shang Gao 008; Ioana Danciu; Eric B. Durbin; Xiao-Cheng Wu; Antoinette Stroup; Jennifer A. Doherty; Stephen M. Schwartz; Charles Wiggins; Mark Damesyn; Linda Coyle; Lynne Penberthy; et al. (J. Biomed. Informatics, 2022)

A Keyword-Enhanced Approach to Handle Class Imbalance in Clinical Text Classification. - Andrew E. Blanchard; Shang Gao 008; Hong-Jun Yoon; James Blair Christian; Eric B. Durbin; Xiao-Cheng Wu; Antoinette Stroup; Jennifer A. Doherty; Stephen M. Schwartz; Charles Wiggins; Linda Coyle; Lynne Penberthy; et al. (IEEE J. Biomed. Health Informatics, 2022)

Enhancing Text Classification Models with Generative AI-aided Data Augmentation. - Huanhuan Zhao; Haihua Chen 002; Hong-Jun Yoon (AITest, 2023)

A comparison of histopathology imaging comprehension algorithms based on multiple instance learning. - Adam Saunders; Sajal Dash; Aristeidis Tsaris; Hong-Jun Yoon (Digital and Computational Pathology, 2023)

Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks. - Aristeidis Tsaris; Joshua Romero; Thorsten Kurth; Jacob D. Hinkle; Hong-Jun Yoon; Feiyi Wang; Sajal Dash; Georgia D. Tourassi (PASC, 2023)

Ultra-Long Sequence Distributed Transformer. - Xiao Wang 004; Isaac Lyngaas; Aristeidis Tsaris; Peng Chen 035; Sajal Dash; Mayanka Chandra Shekar; Tao Luo 014; Hong-Jun Yoon; Mohamed Wahib; John Gounley (CoRR, 2023)

A Decision Support System to Compile Environmental Mitigations from Hydropower Licensing Documents. - Hong-Jun Yoon; Tom Ruggles; Huanhuan Zhao; Debjani Singh (IEEE Big Data, 2024)

Enhancing Diagnosis through AI-driven Analysis of Reflectance Confocal Microscopy. - Hong-Jun Yoon; Chris Keum; Alexander Witkowski; Joanna Ludzik; Tracy Petrie; Heidi A. Hanson; Sancy A. Leachman (CoRR, 2024)

Deep learning uncertainty quantification for clinical text classification. - Alina Peluso; Ioana Danciu; Hong-Jun Yoon; Jamaludin Mohd-Yusof; Tanmoy Bhattacharya 001; Adam Spannaus; Noah Schaefferkoetter; Eric B. Durbin; Xiao-Cheng Wu; Antoinette Stroup; Jennifer A. Doherty; Stephen M. Schwartz; et al. (J. Biomed. Informatics, 2024)

Development of message passing-based graph convolutional networks for classifying cancer pathology reports. - Hong-Jun Yoon; Hilda B. Klasky; Andrew E. Blanchard; James Blair Christian; Eric B. Durbin; Xiao-Cheng Wu; Antoinette Stroup; Jennifer A. Doherty; Linda Coyle; Lynne Penberthy; Georgia D. Tourassi (BMC Medical Informatics Decis. Mak., 2024)

ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling. - Xiao Wang 004; Jong-Youl Choi; Takuya Kurihaya; Isaac Lyngaas; Hong-Jun Yoon; Ming Fan; Nasik Muhammad Nafi; Aristeidis Tsaris; Ashwin M. Aji; Maliha Hossain; Mohamed Wahib; Dali Wang; et al. (CoRR, 2025)

OFCnetLLM: Large Language Model for Network Monitoring and Alertness. - Hong-Jun Yoon; Mariam Kiran; Danial Ebling; Joe Breen (CoRR, 2025)