Tingyi Wanyan

According to our database, Tingyi Wanyan authored at least 14 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Large language models enabled multiagent ensemble method for efficient EHR data labeling.

Jingwei Huang, 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, Donghan M. Yang, Yang Xie

CoRR, 2024

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, Sarah Van Tassel, Yifan Peng

CoRR, 2023

Optimizing Embedding Space with Sub-categorical Supervised Pre-training: A Theoretical Approach Towards Improving Sepsis Prediction.

Tingyi Wanyan, Mingquan Lin, Ying Ding, Benjamin S. Glicksberg, Fei Wang, Yifan Peng

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

2022

Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning.

Junghwan Lee, Tingyi Wanyan, Qingyu Chen, Tiarnan D. L. Keenan, Benjamin S. Glicksberg, Emily Y. Chew, Zhiyong Lu, Fei Wang, Yifan Peng

Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022

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, Zhangyang Wang, Fei Wang, Benjamin S. Glicksberg, Yifan Peng

Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022

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, Benjamin S. Glicksberg

IEEE Trans. Big Data, 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, Girish N. Nadkarni, Marinka Zitnik, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg

Patterns, 2021

Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records.

Tingyi Wanyan, Hossein Honarvar, Ariful Azad, Ying Ding, Benjamin S. Glicksberg

Data Intell., 2021

Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data.

Tingyi Wanyan, Jing Zhang, Ying Ding, Ariful Azad, Zhangyang Wang, Benjamin S. Glicksberg

CoRR, 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, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg

CoRR, 2021

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

Proceedings of the Diversity, Divergence, Dialogue, 2021

2020

Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN.

Tingyi Wanyan, Chenwei Zhang, Ariful Azad, Xiaomin Liang, Daifeng Li, Ying Ding

CoRR, 2020

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, Justin F. Rousseau, Ariful Azad, Ying Ding, Benjamin S. Glicksberg

Proceedings of the Artificial Intelligence in Medicine, 2020

2017

Addressing supply chain risks of microelectronic devices through computer vision.

Zhenhua Chen, Tingyi Wanyan, Ramya Rao, Benjamin Cutilli, James Sowinski, David J. Crandall, Robert Templeman

Proceedings of the 2017 IEEE Applied Imagery Pattern Recognition Workshop, 2017