# 2023 Beijing Health Data Science Summit

**Authors:** Luming Chen, Yifan Qi, Tao Yang, Yao Cheng, Lizong Deng, Taijiao Jiang, Wenjing Zhao, Shuang Wang, Jian Du, Yueying Wu, Liantao Ma, Yasha Wang, Wen Tang, Feifei Zhang, Chao Yang, Fulin Wang, Yuhao Liu, Pengfei Li, Luxia Zhang, Tao Yang, Hengrui Liang, Luming Chen, Yifan Qi, Lizong Deng, Jianxing He, Taijiao Jiang, Peng Wang, Shijia Geng, Shenda Hong, Kangyin Chen, Shuang Fan, Shen-Da Hong, Qi Wen, Hao-Yang Hong, Xiao-Hui Zhang, Lan-Ping Xu, Yu Wang, Chen-Hua Yan, Huan Chen, Yu-Hong Chen, Wei Han, Feng-Rong Wang, Jing-Zhi Wang, Xiao-Jun Huang, Xiao-Dong Mo, Jiahao Min, Zuolin Lu, Yabing Hou, Hongxi Yang, Xiaohe Wang, Chenjie Xu, Ying Li, Nana Peng, Shiyu Wang, Bingli Li, Yiwen Jiang, Di Liu, Fuxiao Li, QingPing Yun, Tengfei Lin, Peng Wu, Jiaxin Cai, Qi Feng, Zhirong Yang, Feng Sha, Jinling Tang, Jun Ma, Wenwen Liu, Yangfan Chai, Jiayu Wang, Guilan Kong, Pengfei Li, Jingyi Wu, Tao Xue, Ji Deng, Shenda Hong, Yaomin Wang, Chenzhe Jin, Yuxi Zhou, Shenda Hong, Lan Lan, Jiawei Luo, Ling Guan, Rui Li, Yilong Wang, Hongan Pan, Qing Li, Pengfei Li, Yipeng Lv, Yan Li, Han Chen, Jiahao Min, Chenjie Xu, Fei Wang, Qing Li, Pengfei Li, He Xu, Wenjian Bi, Yan Zhuang, Luxia Zhang, Yan Zhuang, Luxia Zhang, Jinwei Wang, Ling Pan, Yang Deng, Luxia Zhang, Xuanyu Shi, Zitao Liang, Jian Du, Yongmei Bai, Jian Du, Renfeng Su, Yaolong Chen, Tongyue Shi, Zhilong Zhang, Wentie Liu, Junhua Fang, Jianguo Hao, Shuai Jin, Huiying Zhao, Guilan Kong, Jiahe Tian, Xiang Liu, Hong Chen, Meina Li, Wenya Yu, Jianguo Hao, Qing Li, Guilan Kong, Yifan Duan, Ruiqi Wang, Qing Qian, Haolin Wang, Yu Min, Xingchen Peng, Xiaoyuan Wei, Wenchong He, Chenyu Yang, Beibei Cui, Ke Ju, Fulin Wang, Chao Yang, Feifei Zhang, Pengfei Li, Luxia Zhang, Yinghao Zhu, Jingkun An, Enshen Zhou, Lu An, Junyi Gao, Hao Li, Haoran Feng, Bo Hou, Wen Tang, Chengwei Pan, Liantao Ma, Ning Zhang, Yuzhou Gao, Yinan Du, Yunxia Cao, Dongmei Ji, Weibin Liao, Yanfeng Liao, Zhimin Fan, Jiexuan Zhang, Shuochen Li, Jiarui Yang, Liantao Ma, Jingya Wang, Christina Antza, Xian Shen, Tiffany Gooden, Abd A Tahrani, Deirdre A Lane, Anuradhaa Subramanian, Krishna Gokhale, Nicola J Adderley, Rajendra Surenthirakumaran, Paulo A Lotufo, Yutao Guo, Hao Wang, G. Neil Thomas, Gregory Y. H. Lip, Krishnarajah Nirantharakumar, Jiaming Li, Di Zhang, Li Hou, Shirui Yu, Ziyang Wang, Jiale Nan, Xuemei Yang, Xiaoli Tang, Baihua Luo, Kunwei Li, Yi Hu, Man Li, Hong Shan, Duanduan Chen, Shuaitong Zhang, H. Du, C. Piyawajanusorn, G. Ghislat, P. J. Ballester, Junxian Zhao, Xiaohui Wang, Yaolong Chen, Yue Yu, Yu Yang, Guohui Ding, Qi Zhang, Lulu Sun, Yuqi Liu, Jiahao Zhang, Fengyu Wen, Yike Zhang, Chao Yang, Pengfei Li, Qing Wang, Fuzhong Xue, Luxia Zhang, Yuchen Liu, Wenwen Liu, Jun Ma, Yangfan Chai, Guilan Kong, Han Chen, Zhi Cao, Yabing Hou, Hongxi Yang, Xiaohe Wang, Chenjie Xu, Zhichao Guo, Dan Cui, Jiajun Bao, Kang Wei, Wenya Yu, Haoran Su, Bailin Jiang, Guilan Kong, Yi Feng

PMC · DOI: 10.34133/hds.0112 · 2024-06-07

## TL;DR

The 2023 Beijing Health Data Science Summit highlighted innovative data science applications in healthcare, including AI-based predictive models for diseases like Kawasaki and stroke.

## Contribution

The summit introduced an Abstract Competition showcasing novel AI-driven health data science research from leading institutions.

## Key findings

- An interpretable machine learning model was developed to predict outcomes of childhood Kawasaki disease using electronic health records.
- A population-based study revealed survival disparities linked to mobility patterns in cancer patients.
- A deep learning model was created for real-time prediction of acute stroke development.

## Abstract

The 5th annual Beijing Health Data Science Summit, organized by the National Institute of Health Data Science at Peking University, recently concluded with resounding success. This year, the summit aimed to foster collaboration among researchers, practitioners, and stakeholders in the field of health data science to advance the use of data for better health outcomes.

One significant highlight of this year’s summit was the introduction of the Abstract Competition, organized by Health Data Science, a Science Partner Journal, which focused on the use of cutting-edge data science methodologies, particularly the application of artificial intelligence in the healthcare scenarios. The competition provided a platform for researchers to showcase their groundbreaking work and innovations.

In total, the summit received 61 abstract submissions. Following a rigorous evaluation process by the Abstract Review Committee, eight exceptional abstracts were selected to compete in the final round and give presentations in the Abstract Competition.

The winners of the Abstract Competition are as follows:•First Prize: “Interpretable Machine Learning for Predicting Outcomes of Childhood Kawasaki Disease: Electronic Health Record Analysis” presented by researchers from the Chinese Academy of Medical Sciences, Peking Union Medical College, and Chongqing Medical University (presenter Yifan Duan).•Second Prize: “Survival Disparities among Mobility Patterns of Patients with Cancer: A Population-Based Study” presented by a team from Peking University (presenter Fengyu Wen).•Third Prize: “Deep Learning-Based Real-Time Predictive Model for the Development of Acute Stroke” presented by researchers from Beijing Tiantan Hospital (presenter Lan Lan).

First Prize: “Interpretable Machine Learning for Predicting Outcomes of Childhood Kawasaki Disease: Electronic Health Record Analysis” presented by researchers from the Chinese Academy of Medical Sciences, Peking Union Medical College, and Chongqing Medical University (presenter Yifan Duan).

Second Prize: “Survival Disparities among Mobility Patterns of Patients with Cancer: A Population-Based Study” presented by a team from Peking University (presenter Fengyu Wen).

Third Prize: “Deep Learning-Based Real-Time Predictive Model for the Development of Acute Stroke” presented by researchers from Beijing Tiantan Hospital (presenter Lan Lan).

We extend our heartfelt gratitude to the esteemed panel of judges whose expertise and dedication ensured the fairness and quality of the competition. The judging panel included Jiebo Luo from the University of Rochester (chair), Shenda Hong from Peking University, Xiaozhong Liu from Worcester Polytechnic Institute, Liu Yang from Hong Kong Baptist University, Ma Jianzhu from Tsinghua University, Ting Ma from Harbin Institute of Technology, and Jian Tang from Mila–Quebec Artificial Intelligence Institute. We wish to convey our deep appreciation to Zixuan He and Haoyang Hong for their invaluable assistance in the meticulous planning and execution of the event.

As the 2023 Beijing Health Data Science Summit comes to a close, we look forward to welcoming all participants to join us in 2024. Together, we will continue to advance the frontiers of health data science and work toward a healthier future for all.

## Linked entities

- **Diseases:** Kawasaki disease (MONDO:0012727), cancer (MONDO:0004992)

## Full-text entities

- **Diseases:** Cancer (MESH:D009369), Kawasaki Disease (MESH:D009080), Acute Stroke (MESH:D020521)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

30 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11157085/full.md

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Source: https://tomesphere.com/paper/PMC11157085