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However, inaccurate interpretations lead to misdiagnoses and delay proper treatments. In this work, we built a high-quality Chinese 12-lead resting electrocardiogram dataset with 15,357 records, and called for a community effort to improve the performances of CIE through the China ECG AI Contest 2019. This dataset covers most types of ECG interpretations, including the normal type, 8 common abnormal types, and the other type which includes both uncommon abnormal and noise signals. Based on the Contest, we systematically assessed and analyzed a set of top-performing methods, most of which are deep neural networks, with both their commonalities and characteristics. This study establishes the benchmarks for computerized interpretation of 12-lead resting electrocardiogram and provides insights for the development of new methods.<\/jats:p>","DOI":"10.1007\/s11517-021-02420-z","type":"journal-article","created":{"date-parts":[[2021,10,22]],"date-time":"2021-10-22T09:05:24Z","timestamp":1634893524000},"page":"33-45","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram"],"prefix":"10.1007","volume":"60","author":[{"given":"Zijian","family":"Ding","sequence":"first","affiliation":[]},{"given":"Guijin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Huazhong","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Ping","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Dapeng","family":"Fu","sequence":"additional","affiliation":[]},{"given":"Zhen","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Xinkang","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Xia","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Zhourui","family":"Xia","sequence":"additional","affiliation":[]},{"given":"Chiming","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Wenjie","family":"Cai","sequence":"additional","affiliation":[]},{"given":"Binhang","family":"Yuan","sequence":"additional","affiliation":[]},{"given":"Dongya","family":"Jia","sequence":"additional","affiliation":[]},{"given":"Bo","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Chengbin","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Shan","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Runnan","family":"He","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,10,22]]},"reference":[{"key":"2420_CR1","unstructured":"CEAC 2019 (2019) The Chinese ECG AI Contest 2019. http:\/\/mdi.ids.tsinghua.edu.cn\/. 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