no code implementations • 21 Apr 2024 • Zehao Dong, Muhan Zhang, Yixin Chen
We propose a novel Subgraph Pattern GNN (SPGNN) architecture that incorporates these enhancements.
no code implementations • 11 Feb 2024 • Zehao Dong, Qihang Zhao, Philip R. O. Payne, Michael A Province, Carlos Cruchaga, Muhan Zhang, Tianyu Zhao, Yixin Chen, Fuhai Li
However, we found two major limitations of existing GNNs in omics data analysis, i. e., limited-prediction (diagnosis) accuracy and limited-reproducible biomarker identification capacity across multiple datasets.
no code implementations • 11 Feb 2024 • Zehao Dong, Yixin Chen, Hiram Gay, Yao Hao, Geoffrey D. Hugo, Pamela Samson, Tianyu Zhao
A novel Dose Graph Neural Network (DoseGNN) model is developed for predicting DVHs from the structured graph.
no code implementations • 2 Feb 2024 • Zehao Dong, Yixin Chen, Tianyu Zhao
Dose-Volume Histogram (DVH) prediction is fundamental in radiation therapy that facilitate treatment planning, dose evaluation, plan comparison and etc.
1 code implementation • 27 Sep 2023 • Chenfeng Zhao, Zehao Dong, Yixin Chen, Xuan Zhang, Roger D. Chamberlain
In this paper, we propose GNNHLS, an open-source framework to comprehensively evaluate GNN inference acceleration on FPGAs via HLS, containing a software stack for data generation and baseline deployment, and FPGA implementations of 6 well-tuned GNN HLS kernels.
no code implementations • 1 Sep 2023 • Zehao Dong, Muhan Zhang, Philip R. O. Payne, Michael A Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen
We theoretically reveal the trade-off of expressivity and stability in graph-canonization-enhanced GNNs.
1 code implementation • 31 Aug 2023 • Zehao Dong, Weidong Cao, Muhan Zhang, DaCheng Tao, Yixin Chen, Xuan Zhang
The electronic design automation of analog circuits has been a longstanding challenge in the integrated circuit field due to the huge design space and complex design trade-offs among circuit specifications.
no code implementations • 5 Mar 2023 • Hao liu, Muhan Zhang, Zehao Dong, Lecheng Kong, Yixin Chen, Bradley Fritz, DaCheng Tao, Christopher King
We view time-associated disease prediction as classification tasks at multiple time points.
no code implementations • 19 Sep 2022 • Zehao Dong, Heming Zhang, Yixin Chen, Philip R. O. Payne, Fuhai Li
Synergistic drug combinations provide huge potentials to enhance therapeutic efficacy and to reduce adverse reactions.
1 code implementation • 19 Mar 2022 • Zehao Dong, Muhan Zhang, Fuhai Li, Yixin Chen
In this work, we propose a Parallelizable Attention-based Computation structure Encoder (PACE) that processes nodes simultaneously and encodes DAGs in parallel.
no code implementations • 14 May 2021 • Zehao Dong, Heming Zhang, Yixin Chen, Fuhai Li
Though deep learning algorithms are widely used in the drug synergy prediction problem, it is still an open problem to formulate the prediction model with biological meaning to investigate the mysterious mechanisms of synergy (MoS) for the human-AI collaboration in healthcare systems.