Correction to: Nature Communications https://doi.org/10.1038/s41467-025-58724-3, published online 22 April 2025
In the version of the article initially published, in the “Model construction process” section of the Methods, the text “we employed machine learning algorithms such as logistic regression, boosting, and deep learning to predict over 18500 Phecodes as a multi-label classification problem” should have read “we employed machine learning algorithms such as logistic regression, boosting, and deep learning to predict over 1560 Phecodes as a multi-label classification problem”. This correction has been made to the HTML and PDF versions of the article.
Author information
Author notes
These authors contributed equally: Yukang…
Correction to: Nature Communications https://doi.org/10.1038/s41467-025-58724-3, published online 22 April 2025
In the version of the article initially published, in the “Model construction process” section of the Methods, the text “we employed machine learning algorithms such as logistic regression, boosting, and deep learning to predict over 18500 Phecodes as a multi-label classification problem” should have read “we employed machine learning algorithms such as logistic regression, boosting, and deep learning to predict over 1560 Phecodes as a multi-label classification problem”. This correction has been made to the HTML and PDF versions of the article.
Author information
Author notes
These authors contributed equally: Yukang Jiang, Bingxin Zhao, Xiaopu Wang, Borui Tang.
Authors and Affiliations
Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Yukang Jiang 1.
Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, USA
Bingxin Zhao 1.
School of Management, University of Science and Technology of China, Hefei, AH, China
Xiaopu Wang, Huiyang Peng, Zidan Luo & Xueqin Wang 1.
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Borui Tang, Zhiwen Jiang & Hongtu Zhu 1.
Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, AH, China
Yue Shen & Jie Wang 1.
Alibaba Group, Hangzhou, ZJ, China
Zheng Wang & Jieping Ye 1.
Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Hongtu Zhu 1.
Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Hongtu Zhu 1.
Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Hongtu Zhu 1.
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Hongtu Zhu
Authors
- Yukang Jiang
- Bingxin Zhao
- Xiaopu Wang
- Borui Tang
- Huiyang Peng
- Zidan Luo
- Yue Shen
- Zheng Wang
- Zhiwen Jiang
- Jie Wang
- Jieping Ye
- Xueqin Wang
- Hongtu Zhu
Corresponding authors
Correspondence to Jieping Ye, Xueqin Wang or Hongtu Zhu.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Jiang, Y., Zhao, B., Wang, X. et al. Author Correction: UKB-MDRMF: a multi-disease risk and multimorbidity framework based on UK biobank data. Nat Commun 17, 1061 (2026). https://doi.org/10.1038/s41467-026-68888-1
Published: 28 January 2026
Version of record: 28 January 2026
DOI: https://doi.org/10.1038/s41467-026-68888-1