{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T02:24:58Z","timestamp":1789179898279,"version":"build-2803163510"},"reference-count":32,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"1","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2024,1,2]]},"abstract":"<jats:sec sec-type=\"background\" xml:lang=\"en\">\n            <jats:title>Background<\/jats:title>\n            <jats:p xml:lang=\"en\">Traditional risk evaluation models have been applied to guide public health and clinical practice in various studies. However, the application of existing methods to data sets with missing and censored data, as is often the case in electronic health records, requires additional considerations. We aimed to develop and validate a predictive model that exhibits high performance with data sets that contain missing and censored data.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods and Results<\/jats:title>\n            <jats:p xml:lang=\"en\">This is a retrospective cohort study of coronary heart disease at Weihai Municipal Hospital on unique patients aged 18 to 96\u2009years between 2013 and 2021. A total of 169\u2009692 participants formed our study population, of which 10\u2009895 participants were diagnosed with coronary heart disease. Models were built for the risk of coronary heart disease based on demographic, laboratory, and medical history variables. All complete samples were assigned to the training set (n=110\u2009325), whereas the remaining samples were assigned to the validation set (n=59\u2009367). The area under the receiver operating characteristic curve value was 0.800 (95% CI, 0.794\u20130.805), and the C statistic was 0.796 (95% CI, 0.791\u20130.801) in the derivation cohort, and the corresponding values were 0.837 (95% CI, 0.821\u20130.853) and 0.838 (95% CI, 0.822\u20130.854) in the validation cohort. The calibration curve demonstrated its good calibration ability, and decision curve analysis showed its clinical usefulness.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p xml:lang=\"en\">Our proposed risk prediction model has demonstrated significant effectiveness in handling the complexities of electronic health record data, which often involve extensive missing data and censoring. This approach may offer potential assistance in the use of electronic health records to enhance patient outcomes.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/jaha.123.029400","type":"journal-article","created":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T11:00:30Z","timestamp":1703847630000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":13,"title":["Development and Validation of a Bayesian Network\u2010Based Model for Predicting Coronary Heart Disease Risk From Electronic Health Records"],"prefix":"10.1161","volume":"13","author":[{"given":"Xiaowen","family":"Suo","sequence":"first","affiliation":[{"name":"Department of Biostatistics School of Public Health, Cheeloo College of Medicine, Shandong University Jinan Shandong China"},{"name":"National Institute of Health Data Science of China Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaocheng","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Health Examination Weihai Municipal Hospital affiliated to Shandong University Weihai Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Biostatistics School of Public Health, Cheeloo College of Medicine, Shandong University Jinan Shandong China"},{"name":"National Institute of Health Data Science of China Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6706-2594","authenticated-orcid":false,"given":"Qingxin","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Biostatistics School of Public Health, Cheeloo College of Medicine, Shandong University Jinan Shandong China"},{"name":"National Institute of Health Data Science of China Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9041-9045","authenticated-orcid":false,"given":"Lijie","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Health Management Shandong Sports University Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0378-7956","authenticated-orcid":false,"given":"Fuzhong","family":"Xue","sequence":"additional","affiliation":[{"name":"Department of Biostatistics School of Public Health, Cheeloo College of Medicine, Shandong University Jinan Shandong China"},{"name":"National Institute of Health Data Science of China Jinan Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1161\/circoutcomes.109.910711"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2020.11.010"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1161\/01.cir.0000437741.48606.98"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/0002-9149(76)90061-8"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/s0195-668x(03)00114-3"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.c6624"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1161\/01.cir.97.18.1837"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1136\/jech.2005.044842"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.291.21.2591"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1177\/2047487313516563"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1161\/circulationaha.116.022367"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0174944"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/3127881"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrg3208"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-85066-3_3"},{"key":"e_1_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jval.2019.01.006"},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009730122752"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2003.11.001"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2000.00779.x"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2016.03.009"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1958.10501452"},{"key":"e_1_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2009.08.001"},{"key":"e_1_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2010.03.005"},{"key":"e_1_3_1_25_2","doi-asserted-by":"crossref","unstructured":"Cheng J Bell DA Liu W. 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