Addressing supply chain risks of microelectronic devices through computer vision. - Zhenhua Chen 003; Tingyi Wanyan; Ramya Rao; Benjamin Cutilli; James Sowinski; David J. Crandall; Robert Templeman (AIPR, 2017)

Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions. - Tingyi Wanyan; Martin Kang; Marcus A. Badgeley; Kipp W. Johnson; Jessica K. De Freitas; Fayzan F. Chaudhry; Akhil Vaid; Shan Zhao; Riccardo Miotto; Girish N. Nadkarni; Fei Wang 001; Justin F. Rousseau; et al. (AIME, 2020)

Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN. - Tingyi Wanyan; Chenwei Zhang; Ariful Azad; Xiaomin Liang; Daifeng Li; Ying Ding 001 (CoRR, 2020)

Biomedical Knowledge Graph Refinement and Completion Using Graph Representation Learning and Top-K Similarity Measure. - Islam Akef Ebeid; Majdi Hassan; Tingyi Wanyan; Jack Roper; Abhik Seal; Ying Ding 001 (iConference (1), 2021)

Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients. - Tingyi Wanyan; Hossein Honarvar; Suraj K. Jaladanki; Chengxi Zang; Nidhi Naik; Sulaiman Somani; Jessica K. De Freitas; Ishan Paranjpe; Akhil Vaid; Riccardo Miotto; Girish N. Nadkarni; Marinka Zitnik; et al. (CoRR, 2021)

Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data. - Tingyi Wanyan; Jing Zhang; Ying Ding 001; Ariful Azad; Zhangyang Wang; Benjamin S. Glicksberg (CoRR, 2021)

Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records. - Tingyi Wanyan; Hossein Honarvar; Ariful Azad; Ying Ding 001; Benjamin S. Glicksberg (Data Intell., 2021)

Contrastive learning improves critical event prediction in COVID-19 patients. - Tingyi Wanyan; Hossein Honarvar; Suraj K. Jaladanki; Chengxi Zang; Nidhi Naik; Sulaiman Somani; Jessica K. De Freitas; Ishan Paranjpe; Akhil Vaid; Jing Zhang; Riccardo Miotto; Zhangyang Wang; et al. (Patterns, 2021)

Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit. - Tingyi Wanyan; Akhil Vaid; Jessica K. De Freitas; Sulaiman Somani; Riccardo Miotto; Girish N. Nadkarni; Ariful Azad; Ying Ding 001; Benjamin S. Glicksberg (IEEE Trans. Big Data, 2021)

Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction. - Tingyi Wanyan; Mingquan Lin; Eyal Klang; Kartikeya M. Menon; Faris F. Gulamali; Ariful Azad; Yiye Zhang; Ying Ding 001; Zhangyang Wang; Fei Wang 001; Benjamin S. Glicksberg; Yifan Peng 002 (BCB, 2022)

Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning. - Junghwan Lee; Tingyi Wanyan; Qingyu Chen 001; Tiarnan D. L. Keenan; Benjamin S. Glicksberg; Emily Y. Chew; Zhiyong Lu; Fei Wang 001; Yifan Peng 002 (MLMI@MICCAI, 2022)

Optimizing Embedding Space with Sub-categorical Supervised Pre-training: A Theoretical Approach Towards Improving Sepsis Prediction. - Tingyi Wanyan; Mingquan Lin; Ying Ding 001; Benjamin S. Glicksberg; Fei Wang 001; Yifan Peng 002 (ICHI, 2023)

Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served patient populations. - Mingquan Lin; Yuyun Xiao; Bo-Jian Hou; Tingyi Wanyan; Mohit Manoj Sharma; Zhangyang Wang; Fei Wang 001; Sarah Van Tassel; Yifan Peng 002 (CoRR, 2023)

Large language models enabled multiagent ensemble method for efficient EHR data labeling. - Jingwei Huang 002; Kuroush Nezafati; Ismael Villanueva-Miranda; Zifan Gu; Ann Marie Navar; Tingyi Wanyan; Qin Zhou; Bo Yao; Ruichen Rong; Xiaowei Zhan; Guanghua Xiao; Eric D. Peterson; et al. (CoRR, 2024)