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Chen J, Huang S, Zhang Y, Chang Q, Zhang Y, Li D, Qiu J, Hu L, Peng X, Du Y, Gao Y, Chen DZ, Bellou A, Wu J, Liang H. Congenital heart disease detection by pediatric electrocardiogram based deep learning integrated with human concepts. Nat Commun 2024; 15:976. [PMID: 38302502 PMCID: PMC10834950 DOI: 10.1038/s41467-024-44930-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 01/10/2024] [Indexed: 02/03/2024] Open
Abstract
Early detection is critical to achieving improved treatment outcomes for child patients with congenital heart diseases (CHDs). Therefore, developing effective CHD detection techniques using low-cost and non-invasive pediatric electrocardiogram are highly desirable. We propose a deep learning approach for CHD detection, CHDdECG, which automatically extracts features from pediatric electrocardiogram and wavelet transformation characteristics, and integrates them with key human-concept features. Developed on 65,869 cases, CHDdECG achieved ROC-AUC of 0.915 and specificity of 0.881 on a real-world test set covering 12,000 cases. Additionally, on two external test sets with 7137 and 8121 cases, the overall ROC-AUC were 0.917 and 0.907 while specificities were 0.937 and 0.907. Notably, CHDdECG surpassed cardiologists in CHD detection performance comparison, and feature importance scores suggested greater influence of automatically extracted electrocardiogram features on CHD detection compared with human-concept features, implying that CHDdECG may grasp some knowledge beyond human cognition. Our study directly impacts CHD detection with pediatric electrocardiogram and demonstrates the potential of pediatric electrocardiogram for broader benefits.
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Affiliation(s)
- Jintai Chen
- State Key Laboratory of Transvascular Implantation Devices of the Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, 310009, Hangzhou, China
| | - Shuai Huang
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China
| | - Ying Zhang
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Department of Cardiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
| | - Qing Chang
- Liaoning Engineering Research Center of Intelligent Diagnosis and Treatment Ecosystem, 110004, Shenyang, Liaoning Province, China
- Clinical Research Center of Shengjing Hospital of China Medical University, 110004, Shenyang, Liaoning Province, China
| | - Yixiao Zhang
- Liaoning Engineering Research Center of Intelligent Diagnosis and Treatment Ecosystem, 110004, Shenyang, Liaoning Province, China
- Department of Urology Surgery, Shengjing Hospital of China Medical University, 110004, Shenyang, Liaoning Province, China
| | - Dantong Li
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China
| | - Jia Qiu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Department of Cardiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
| | - Lianting Hu
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China
| | - Xiaoting Peng
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China
| | - Yunmei Du
- College of Information Technology and Engineering, Guangzhou College of Commerce, 510363, Guangzhou, Guangdong Province, China
- Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 510623, Guangzhou, Guangdong Province, China
| | - Yunfei Gao
- Zhuhai Precision Medical Center, Zhuhai People's Hospital/ Zhuhai Hospital Affiliated with Jinan University, Jinan University, 519000, Zhuhai, Guangdong Province, China
- The Biomedical Translational Research Institute, Jinan University Faculty of Medical Science, Jinan University, 510632, Guangzhou, Guangdong Province, China
| | - Danny Z Chen
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Abdelouahab Bellou
- Institute of Sciences in Emergency Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, China.
- Department of Emergency Medicine, Wayne State University School of Medicine, Detroit, MI, 48201, USA.
| | - Jian Wu
- State Key Laboratory of Transvascular Implantation Devices of the Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, 310009, Hangzhou, China.
- School of Public Health, Zhejiang University, 310058, Hangzhou, China.
| | - Huiying Liang
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 510080, Guangzhou, Guangdong Province, China.
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong Province, China.
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), 510080, Guangzhou, Guangdong Province, China.
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Khairy P, Van Hare GF, Balaji S, Berul CI, Cecchin F, Cohen MI, Daniels CJ, Deal BJ, Dearani JA, Groot ND, Dubin AM, Harris L, Janousek J, Kanter RJ, Karpawich PP, Perry JC, Seslar SP, Shah MJ, Silka MJ, Triedman JK, Walsh EP, Warnes CA. PACES/HRS expert consensus statement on the recognition and management of arrhythmias in adult congenital heart disease: developed in partnership between the Pediatric and Congenital Electrophysiology Society (PACES) and the Heart Rhythm Society (HRS). Endorsed by the governing bodies of PACES, HRS, the American College of Cardiology (ACC), the American Heart Association (AHA), the European Heart Rhythm Association (EHRA), the Canadian Heart Rhythm Society (CHRS), and the International Society for Adult Congenital Heart Disease (ISACHD). Can J Cardiol 2014; 30:e1-e63. [PMID: 25262867 DOI: 10.1016/j.cjca.2014.09.002] [Citation(s) in RCA: 151] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
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