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Tingyi Wanyan
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2020 – today
- 2023
- [c6]Tingyi Wanyan, Mingquan Lin, Ying Ding, Benjamin S. Glicksberg, Fei Wang, Yifan Peng:
Optimizing Embedding Space with Sub-categorical Supervised Pre-training: A Theoretical Approach Towards Improving Sepsis Prediction. ICHI 2023: 101-110 - [i6]Mingquan Lin, Yuyun Xiao, Bo-Jian Hou, Tingyi Wanyan, Mohit Manoj Sharma, Zhangyang Wang, Fei Wang, Sarah Van Tassel, Yifan Peng:
Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served patient populations. CoRR abs/2301.11315 (2023) - 2022
- [c5]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:
Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction. BCB 2022: 9:1-9:9 - [c4]Junghwan Lee, Tingyi Wanyan, Qingyu Chen, Tiarnan D. L. Keenan, Benjamin S. Glicksberg, Emily Y. Chew, Zhiyong Lu, Fei Wang, Yifan Peng:
Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning. MLMI@MICCAI 2022: 11-20 - 2021
- [j3]Tingyi Wanyan, Hossein Honarvar, Ariful Azad, Ying Ding, Benjamin S. Glicksberg:
Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records. Data Intell. 3(3): 329-339 (2021) - [j2]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:
Contrastive learning improves critical event prediction in COVID-19 patients. Patterns 2(12): 100389 (2021) - [j1]Tingyi Wanyan, Akhil Vaid, Jessica K. De Freitas, Sulaiman Somani, Riccardo Miotto, Girish N. Nadkarni, Ariful Azad, Ying Ding, Benjamin S. Glicksberg:
Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit. IEEE Trans. Big Data 7(1): 38-44 (2021) - [c3]Islam Akef Ebeid, Majdi Hassan, Tingyi Wanyan, Jack Roper, Abhik Seal, Ying Ding:
Biomedical Knowledge Graph Refinement and Completion Using Graph Representation Learning and Top-K Similarity Measure. iConference (1) 2021: 112-123 - [i5]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:
Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients. CoRR abs/2101.04013 (2021) - [i4]Tingyi Wanyan, Jing Zhang, Ying Ding, Ariful Azad, Zhangyang Wang, Benjamin S. Glicksberg:
Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data. CoRR abs/2104.02932 (2021) - 2020
- [c2]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:
Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions. AIME 2020: 14-25 - [i3]Tingyi Wanyan, Chenwei Zhang, Ariful Azad, Xiaomin Liang, Daifeng Li, Ying Ding:
Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN. CoRR abs/2004.01375 (2020) - [i2]Islam Akef Ebeid, Majdi Hassan, Tingyi Wanyan, Jack Roper, Abhik Seal, Ying Ding:
Biomedical Knowledge Graph Refinement and Completion using Graph Representation Learning and Top-K Similarity Measure. CoRR abs/2012.10540 (2020) - [i1]Tingyi Wanyan, Hossein Honarvar, Ariful Azad, Ying Ding, Benjamin S. Glicksberg:
Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records. CoRR abs/2012.14065 (2020)
2010 – 2019
- 2017
- [c1]Zhenhua Chen, Tingyi Wanyan, Ramya Rao, Benjamin Cutilli, James Sowinski, David J. Crandall, Robert Templeman:
Addressing supply chain risks of microelectronic devices through computer vision. AIPR 2017: 1-8
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