Prediction of chronic kidney disease risk using multimodal data-Reference-Cited by-同舟云学术

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Prediction of chronic kidney disease risk using multimodal data

Published:2021-02-02 Issue: Volume: Page:
ISSN:
Container-title:2021 The 5th International Conference on Compute and Data Analysis
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Author:

Ma Dongfang¹,Li Ximin²,Mou Shenghong¹,Cheng Zhiyuan¹,Yan Xiaoqian³,Lu Ying³,Yan Ruijian⁴,Cao Shiyue¹

Affiliation:

1. School of Micro-Nanoelectronics,Zhejiang University, China

2. Second Clinical Medical College Zhejiang Chinese Medical University, China

3. Tongde Hospital of Zhejiang Province, China

4. Department of Orthopedic Surgery Second Affiliated Hospital Zhejiang University School of Medicine, China

Funder

Natural Science Foundation of Zhejiang Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3456529.3456533

Reference33 articles.

1. Risk Models to Predict Chronic Kidney Disease and Its Progression: A Systematic Review

2. A Simple Algorithm to Predict Incident Kidney Disease

3. Aljaaf A J Al-Jumeily D Haglan H M Early Prediction of Chronic Kidney Disease Using Machine Learning Supported by Predictive Analytics[J]. 2018:1-9. Aljaaf A J Al-Jumeily D Haglan H M Early Prediction of Chronic Kidney Disease Using Machine Learning Supported by Predictive Analytics[J]. 2018:1-9.

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Application of visual transformer in renal image analysis;BioMedical Engineering OnLine;2024-03-05

2. Deep learning prediction models based on EHR trajectories: A systematic review;Journal of Biomedical Informatics;2023-08

3. Recent Advances and Future Perspectives in the Use of Machine Learning and Mathematical Models in Nephrology;Advances in Chronic Kidney Disease;2022-09

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