{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,3,23]],"date-time":"2024-03-23T11:17:17Z","timestamp":1711192637611},"reference-count":81,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T00:00:00Z","timestamp":1676419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"name":"Chang Gung Memorial Hospital Research","award":["CRRPG2H0065","CLRPG2L0052"],"award-info":[{"award-number":["CRRPG2H0065","CLRPG2L0052"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Estimating the deterioration paths of chronic hepatitis B (CHB) patients is critical for physicians\u2019 decisions and patient management. A novel, hierarchical multilabel graph attention-based method aims to predict patient deterioration paths more effectively. Applied to a CHB patient data set, it offers strong predictive utilities and clinical value.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>The proposed method incorporates patients\u2019 responses to medications, diagnosis event sequences, and outcome dependencies to estimate deterioration paths. From the electronic health records maintained by a major healthcare organization in Taiwan, we collect clinical data about 177\u200a959 patients diagnosed with hepatitis B virus infection. We use this sample to evaluate the proposed method\u2019s predictive efficacy relative to 9 existing methods, as measured by precision, recall, F-measure, and area under the curve (AUC).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We use 20% of the sample as holdouts to test each method\u2019s prediction performance. The results indicate that our method consistently and significantly outperforms all benchmark methods. It attains the highest AUC, with a 4.8% improvement over the best-performing benchmark, as well as 20.9% and 11.4% improvements in precision and F-measures, respectively. The comparative results demonstrate that our method is more effective for predicting CHB patients\u2019 deterioration paths than existing predictive methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion and Conclusion<\/jats:title>\n                  <jats:p>The proposed method underscores the value of patient-medication interactions, temporal sequential patterns of distinct diagnosis, and patient outcome dependencies for capturing dynamics that underpin patient deterioration over time. Its efficacious estimates grant physicians a more holistic view of patient progressions and can enhance their clinical decision-making and patient management.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocad008","type":"journal-article","created":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T10:23:11Z","timestamp":1676542991000},"page":"846-858","source":"Crossref","is-referenced-by-count":1,"title":["A hierarchical multilabel graph attention network method to predict the deterioration paths of chronic hepatitis B patients"],"prefix":"10.1093","volume":"30","author":[{"given":"Zejian (Eric)","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Operations and Information Systems, David Eccles School of Business, University of Utah , Salt Lake City, Utah, USA"}]},{"given":"Da","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Information Systems, College of Business, California State University Long Beach , Long Beach, California, USA"}]},{"given":"Paul Jen-Hwa","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Operations and Information Systems, David Eccles School of Business, University of Utah , Salt Lake City, Utah, USA"}]},{"given":"Ting-Shuo","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Keelung Chang Gung Memorial Hospital , Keelung City, Taiwan"},{"name":"Department of Chinese Medicine, College of Medicine, Chang Gung University , Taoyuan City, Taiwan"},{"name":"Community Medicine Research Center, Keelung Chang Gung Memorial Hospital , Keelung City, Taiwan"}]}],"member":"286","published-online":{"date-parts":[[2023,2,15]]},"reference":[{"issue":"17","key":"2023041909010512700_ocad008-B1","doi-asserted-by":"crossref","first-page":"1802","DOI":"10.1001\/jama.2018.3795","article-title":"Chronic hepatitis B infection: a review","volume":"319","author":"Tang","year":"2018","journal-title":"JAMA"},{"issue":"1 Pt 1","key":"2023041909010512700_ocad008-B2","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.jfma.2018.11.008","article-title":"Taiwan consensus statement on the management of chronic hepatitis B","volume":"118","author":"Chien","year":"2019","journal-title":"J Formos Med Assoc"},{"key":"2023041909010512700_ocad008-B3","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1136\/bmj.322.7279.151","article-title":"ABC of diseases of liver, pancreas, and biliary system: acute hepatitis","volume":"322","author":"Ryder","year":"2001","journal-title":"BMJ"},{"key":"2023041909010512700_ocad008-B4"},{"issue":"10161","key":"2023041909010512700_ocad008-B5","doi-asserted-by":"crossref","first-page":"2313","DOI":"10.1016\/S0140-6736(18)31865-8","article-title":"Chronic hepatitis B virus infection","volume":"392","author":"Seto","year":"2018","journal-title":"Lancet"},{"issue":"10","key":"2023041909010512700_ocad008-B6","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1038\/s41575-020-0296-6","article-title":"The evolution and clinical impact of hepatitis B virus genome diversity","volume":"17","author":"Revill","year":"2020","journal-title":"Nat Rev Gastroenterol Hepatol"},{"key":"2023041909010512700_ocad008-B7","doi-asserted-by":"crossref","first-page":"104783","DOI":"10.1016\/j.antiviral.2020.104783","article-title":"Reasons to consider early treatment in chronic hepatitis B patients","volume":"177","author":"Koffas","year":"2020","journal-title":"Antiviral Res"},{"issue":"11","key":"2023041909010512700_ocad008-B8","doi-asserted-by":"crossref","first-page":"6229","DOI":"10.1002\/jmv.27114","article-title":"The relationship between liver pathological inflammation degree and pyroptosis in chronic hepatitis B patients","volume":"93","author":"Wang","year":"2021","journal-title":"J Med Virol"},{"key":"2023041909010512700_ocad008-B9","doi-asserted-by":"crossref","first-page":"S1","DOI":"10.1016\/S1386-6532(05)00384-7","article-title":"Worldwide epidemiology of HBV infection, disease burden, and vaccine prevention","volume":"34","author":"Lavanchy","year":"2015","journal-title":"J Clin Virol"},{"issue":"1","key":"2023041909010512700_ocad008-B10","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.jhep.2018.09.014","article-title":"Burden of liver diseases in the world","volume":"70","author":"Asrani","year":"2019","journal-title":"J Hepatol"},{"issue":"3","key":"2023041909010512700_ocad008-B11","doi-asserted-by":"crossref","first-page":"47","DOI":"10.15585\/mmwr.mm6503a2","article-title":"Increases in acute hepatitis B virus infections-Kentucky, Tennessee, and West Virginia, 2006\u20132013","volume":"65","author":"Harris","year":"2016","journal-title":"MMWR Morb Mortal Wkly Rep"},{"issue":"1","key":"2023041909010512700_ocad008-B12","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.jhep.2020.01.027","article-title":"Hepatitis B-related outcomes following direct-acting antiviral therapy in Taiwanese patients with chronic HBV\/HCV co-infection","volume":"73","author":"Yeh","year":"2020","journal-title":"J Hepatol"},{"issue":"12","key":"2023041909010512700_ocad008-B13","doi-asserted-by":"crossref","first-page":"2655","DOI":"10.3390\/ijerph15122655","article-title":"Treatment and cost of hepatocellular carcinoma: a population-based cohort study in Taiwan","volume":"15","author":"Nguang","year":"2018","journal-title":"Int J Environ Res Public Health"},{"issue":"1","key":"2023041909010512700_ocad008-B14","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1093\/epirev\/mxj010","article-title":"Nationwide hepatitis b vaccination program in Taiwan: effectiveness in the 20 years after it was launched","volume":"28","author":"Chien","year":"2006","journal-title":"Epidemiol Rev"},{"issue":"1","key":"2023041909010512700_ocad008-B15","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.jhep.2018.09.021","article-title":"Healthcare resource utilization and costs by disease severity in an insured national sample of US patients with chronic hepatitis B","volume":"70","author":"Nguyen","year":"2019","journal-title":"J Hepatol"},{"issue":"8","key":"2023041909010512700_ocad008-B16","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1016\/j.resuscitation.2013.01.013","article-title":"Defining clinical deterioration","volume":"84","author":"Jones","year":"2013","journal-title":"Resuscitation"},{"issue":"6","key":"2023041909010512700_ocad008-B17","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1111\/j.1440-1746.2005.03813.x","article-title":"Chronic hepatitis B virus infection in the Asia\u2013Pacific region and Africa: review of disease progression","volume":"20","author":"Lin","year":"2005","journal-title":"J Gastroenterol Hepatol"},{"issue":"5","key":"2023041909010512700_ocad008-B18","first-page":"314","article-title":"Hepatitis B: screening, prevention, diagnosis, and treatment","volume":"99","author":"Wilkins","year":"2019","journal-title":"Am Fam Physician"},{"issue":"37","key":"2023041909010512700_ocad008-B19","doi-asserted-by":"crossref","first-page":"8314","DOI":"10.3748\/wjg.v22.i37.8314","article-title":"Prediction models of hepatocellular carcinoma development in chronic hepatitis B patients","volume":"22","author":"Lee","year":"2016","journal-title":"World J Gastroenterol"},{"issue":"3","key":"2023041909010512700_ocad008-B20","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1111\/liv.14334","article-title":"Clinical utility of hepatocellular carcinoma risk scores in chronic hepatitis B","volume":"40","author":"Voulgaris","year":"2020","journal-title":"Liver Int"},{"issue":"2","key":"2023041909010512700_ocad008-B21","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.jhep.2021.09.025","article-title":"An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B","volume":"76","author":"Kim","year":"2022","journal-title":"J Hepatol"},{"issue":"4","key":"2023041909010512700_ocad008-B22","doi-asserted-by":"crossref","first-page":"e19812","DOI":"10.2196\/19812","article-title":"Predicting hepatocellular carcinoma with minimal features from electronic health records: development of a deep learning model","volume":"7","author":"Liang","year":"2021","journal-title":"JMIR Cancer"},{"issue":"3","key":"2023041909010512700_ocad008-B23","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1111\/jgh.15415","article-title":"Artificial intelligence in precision medicine in hepatology","volume":"36","author":"Su","year":"2021","journal-title":"J Gastroenterol Hepatol"},{"issue":"1","key":"2023041909010512700_ocad008-B24","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1097\/MEG.0000000000001592","article-title":"Dynamic prediction of liver cirrhosis risk in chronic hepatitis B patients using longitudinal clinical data","volume":"32","author":"Wang","year":"2020","journal-title":"Eur J Gastroenterol Hepatol"},{"issue":"6","key":"2023041909010512700_ocad008-B25","doi-asserted-by":"crossref","first-page":"100175","DOI":"10.1016\/j.jhepr.2020.100175","article-title":"Deep learning model for prediction of hepatocellular carcinoma in patients with HBV-related cirrhosis on antiviral therapy","volume":"2","author":"Nam","year":"2020","journal-title":"JHEP Rep"},{"issue":"12","key":"2023041909010512700_ocad008-B26","doi-asserted-by":"crossref","first-page":"2499","DOI":"10.1016\/j.cgh.2021.02.040","article-title":"Hepatocellular carcinoma prediction models in chronic hepatitis B: a systematic review of 14 models and external validation","volume":"19","author":"Wu","year":"2021","journal-title":"Clin Gastroenterol Hepatol"},{"issue":"3","key":"2023041909010512700_ocad008-B27","doi-asserted-by":"crossref","first-page":"228","DOI":"10.3350\/cmh.2014.20.3.228","article-title":"Prediction of fibrosis progression in chronic viral hepatitis","volume":"20","author":"Wong","year":"2014","journal-title":"Clin Mol Hepatol"},{"issue":"5","key":"2023041909010512700_ocad008-B28","doi-asserted-by":"crossref","first-page":"e0116","DOI":"10.1097\/CCE.0000000000000116","article-title":"Early detection of in-patient deterioration: one prediction model does not fit all","volume":"2","author":"Blackwell","year":"2020","journal-title":"Crit Care Explor"},{"issue":"3","key":"2023041909010512700_ocad008-B29","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.ymeth.2014.01.021","article-title":"Deciphering early development of complex diseases by progressive module network","volume":"67","author":"Zeng","year":"2014","journal-title":"Methods"},{"issue":"1","key":"2023041909010512700_ocad008-B30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12976-017-0057-6","article-title":"Markov modeling in hepatitis B screening and linkage to care","volume":"14","author":"Sehr","year":"2017","journal-title":"Theor Biol Med Model"},{"issue":"5","key":"2023041909010512700_ocad008-B31","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1111\/j.1524-4733.2010.00733.x","article-title":"Cost-effectiveness of nucleoside analog therapy for hepatitis B in China: a Markov analysis","volume":"13","author":"Wu","year":"2010","journal-title":"Value Health"},{"issue":"8","key":"2023041909010512700_ocad008-B32","doi-asserted-by":"crossref","first-page":"1997","DOI":"10.3390\/molecules25081997","article-title":"Viral hepatitis and iron dysregulation: molecular pathways and the role of lactoferrin","volume":"25","author":"Mancinelli","year":"2020","journal-title":"Molecules"},{"issue":"2","key":"2023041909010512700_ocad008-B33","doi-asserted-by":"crossref","first-page":"108","DOI":"10.3350\/cmh.2017.0068","article-title":"Management of chronic hepatitis B patients in immunetolerant phase: what latest guidelines recommend","volume":"24","author":"Wong","year":"2018","journal-title":"Clin Mol Hepatol"},{"key":"2023041909010512700_ocad008-B34","year":"2017"},{"issue":"24","key":"2023041909010512700_ocad008-B35","doi-asserted-by":"crossref","first-page":"1733","DOI":"10.1056\/NEJM199712113372406","article-title":"Hepatitis B: virus infection","volume":"337","author":"Lee","year":"1997","journal-title":"N Engl J Med"},{"issue":"10308","key":"2023041909010512700_ocad008-B36","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.1016\/S0140-6736(21)01374-X","article-title":"Liver cirrhosis","volume":"398","author":"Gin\u00e8s","year":"2021","journal-title":"Lancet"},{"issue":"2","key":"2023041909010512700_ocad008-B37","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.jhep.2007.11.011","article-title":"Natural history of chronic hepatitis B: special emphasis on disease progression and prognostic factors","volume":"48","author":"Fattovich","year":"2008","journal-title":"J Hepatol"},{"issue":"3","key":"2023041909010512700_ocad008-B38","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1002\/cam4.1998","article-title":"Real impact of liver cirrhosis on the development of hepatocellular carcinoma in various liver diseases\u2014meta-analytic assessment","volume":"8","author":"Tarao","year":"2019","journal-title":"Cancer Med"},{"issue":"8","key":"2023041909010512700_ocad008-B39","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1080\/00365521.2019.1649454","article-title":"Risk and outcome of hepatocellular carcinoma in liver cirrhosis in Southern Sweden: a population-based study","volume":"54","author":"Nilsson","year":"2019","journal-title":"Scand J Gastroenterol"},{"key":"2023041909010512700_ocad008-B40","doi-asserted-by":"crossref","first-page":"131","DOI":"10.2147\/JHC.S159269","article-title":"Status of, and strategies for improving, adherence to HCC screening and surveillance","volume":"6","author":"Francica","year":"2019","journal-title":"J Hepatocell Carcinoma"},{"issue":"6","key":"2023041909010512700_ocad008-B41","doi-asserted-by":"crossref","first-page":"1098","DOI":"10.1093\/jamia\/ocaa277","article-title":"Machine-learning model to predict the cause of death using a stacking ensemble method for observational data","volume":"28","author":"Kim","year":"2021","journal-title":"J Am Med Inform Assoc"},{"issue":"1","key":"2023041909010512700_ocad008-B42","first-page":"1","article-title":"High-dimensional hepatopath data analysis by machine learning for predicting HBV-related fibrosis","volume":"11","author":"Pu","year":"2021","journal-title":"Sci Rep"},{"key":"2023041909010512700_ocad008-B43","volume-title":"Statistics for Healthcare Professionals: An Introduction","author":"Scott","year":"2014"},{"issue":"15","key":"2023041909010512700_ocad008-B44","doi-asserted-by":"crossref","first-page":"1553","DOI":"10.1001\/jama.2011.451","article-title":"A predictive model for progression of chronic kidney disease to kidney failure","volume":"305","author":"Tangri","year":"2011","journal-title":"JAMA"},{"key":"2023041909010512700_ocad008-B45","first-page":"1095","article-title":"Modeling disease progression via fused sparse group lasso","volume":"2012","author":"Zhou","year":"2012","journal-title":"KDD"},{"issue":"2","key":"2023041909010512700_ocad008-B46","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1093\/jamia\/ocw112","article-title":"Using recurrent neural network models for early detection of heart failure onset","volume":"24","author":"Choi","year":"2017","journal-title":"J Am Med Inform Assoc"},{"issue":"1","key":"2023041909010512700_ocad008-B47","doi-asserted-by":"crossref","first-page":"12024","DOI":"10.1088\/1742-6596\/1255\/1\/012024","article-title":"Chronic kidney disease prediction by using different decision tree techniques","volume":"1255","author":"Pasadana","year":"2019","journal-title":"J Phys Conf Ser"},{"issue":"4","key":"2023041909010512700_ocad008-B48","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1093\/jamia\/ocaa336","article-title":"Predicting pressure injury using nursing assessment phenotypes and machine learning methods","volume":"28","author":"Song","year":"2021","journal-title":"J Am Med Inform Assoc"},{"issue":"3","key":"2023041909010512700_ocad008-B49","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1093\/jamia\/ocz211","article-title":"On classifying sepsis heterogeneity in the ICU: insight using machine learning","volume":"27","author":"Ibrahim","year":"2020","journal-title":"J Am Med Inform Assoc"},{"issue":"8","key":"2023041909010512700_ocad008-B50","doi-asserted-by":"crossref","first-page":"e0202344","DOI":"10.1371\/journal.pone.0202344","article-title":"Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease","volume":"13","author":"Steele","year":"2018","journal-title":"PLoS One"},{"key":"2023041909010512700_ocad008-B51","first-page":"168","author":"Lu","year":"2022"},{"key":"2023041909010512700_ocad008-B52","author":"Xu"},{"key":"2023041909010512700_ocad008-B53","volume-title":"International Conference on Learning Representations (ICLR)","author":"Veli\u010dkovi\u0107"},{"key":"2023041909010512700_ocad008-B54","volume-title":"International Conference on Learning Representations (ICLR)","author":"Kipf"},{"issue":"1","key":"2023041909010512700_ocad008-B55","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40649-019-0069-y","article-title":"Graph convolutional networks: a comprehensive review","volume":"6","author":"Zhang","year":"2019","journal-title":"Comput Soc Netw"},{"key":"2023041909010512700_ocad008-B56","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume":"2017","author":"Hamilton"},{"issue":"9","key":"2023041909010512700_ocad008-B57","doi-asserted-by":"crossref","first-page":"1343","DOI":"10.1093\/jamia\/ocaa120","article-title":"Predicting complications of diabetes mellitus using advanced machine learning algorithms","volume":"27","author":"Ljubic","year":"2020","journal-title":"J Am Med Inform Assoc"},{"issue":"10","key":"2023041909010512700_ocad008-B58","doi-asserted-by":"crossref","first-page":"2155","DOI":"10.1093\/jamia\/ocab109","article-title":"Interpretable disease prediction using heterogeneous patient records with self-attentive fusion encoder","volume":"28","author":"Kwak","year":"2021","journal-title":"J Am Med Inform Assoc"},{"issue":"1","key":"2023041909010512700_ocad008-B59","first-page":"1","article-title":"BEHRT: transformer for electronic health records","volume":"10","author":"Li","year":"2020","journal-title":"Sci Rep"},{"issue":"20","key":"2023041909010512700_ocad008-B60","doi-asserted-by":"crossref","first-page":"7781","DOI":"10.1002\/cam4.3421","article-title":"Reduced liver cancer mortality with regular clinic follow-up among patients with chronic hepatitis B: a nationwide cohort study","volume":"9","author":"Shim","year":"2020","journal-title":"Cancer Med"},{"issue":"1","key":"2023041909010512700_ocad008-B61","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/srep32404","article-title":"Large-scale discovery of disease-disease and disease-gene associations","volume":"6","author":"Gligorijevic","year":"2016","journal-title":"Sci Rep"},{"issue":"1","key":"2023041909010512700_ocad008-B62","first-page":"606","article-title":"Learning the graphical structure of electronic health records with graph convolutional transformer","volume":"34","author":"Choi","year":"2020","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"2023041909010512700_ocad008-B63","volume-title":"12th International Conference on Agents and Artificial Intelligence (ICAART)","author":"Pal"},{"key":"2023041909010512700_ocad008-B64","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J Artif Intell Res"},{"issue":"4","key":"2023041909010512700_ocad008-B65","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1093\/jamia\/ocaa306","article-title":"Importance-aware personalized learning for early risk prediction using static and dynamic health data","volume":"28","author":"Tan","year":"2021","journal-title":"J Am Med Inform Assoc"},{"issue":"6","key":"2023041909010512700_ocad008-B66","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1093\/jamia\/ocab003","article-title":"Development of a novel machine learning model to predict presence of nonalcoholic steatohepatitis","volume":"28","author":"Docherty","year":"2021","journal-title":"J Am Med Inform Assoc"},{"issue":"8","key":"2023041909010512700_ocad008-B67","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.1093\/jamia\/ocab043","article-title":"Identifying risk of opioid use disorder for patients taking opioid medications with deep learning","volume":"28","author":"Dong","year":"2021","journal-title":"J Am Med Inform Assoc"},{"issue":"e1","key":"2023041909010512700_ocad008-B68","doi-asserted-by":"crossref","first-page":"e40","DOI":"10.1093\/jamia\/ocw097","article-title":"Congestive heart failure information extraction framework for automated treatment performance measures assessment","volume":"24","author":"Meystre","year":"2017","journal-title":"J Am Med Inform Assoc"},{"key":"2023041909010512700_ocad008-B69","volume-title":"arXiv preprint arXiv:2008.05756","author":"Grandini"},{"issue":"11","key":"2023041909010512700_ocad008-B70","first-page":"7747","article-title":"Learning with multiclass AUC: theory and algorithms","volume":"44","author":"Yang","year":"2022"},{"issue":"5","key":"2023041909010512700_ocad008-B71","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1093\/jamia\/ocac003","article-title":"Integrating landmark modeling framework and machine learning algorithms for dynamic prediction of tuberculosis treatment outcomes","volume":"29","author":"Kheirandish","year":"2022","journal-title":"J Am Med Inform Assoc"},{"key":"2023041909010512700_ocad008-B72","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/j.ins.2019.11.004","article-title":"Data imbalance in classification: experimental evaluation","volume":"513","author":"Thabtah","year":"2020","journal-title":"Inf Sci"},{"issue":"3","key":"2023041909010512700_ocad008-B73","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1109\/TNB.2018.2837622","article-title":"Deep patient similarity learning for personalized healthcare","volume":"17","author":"Suo","year":"2018","journal-title":"IEEE Trans Nanobioscience"},{"key":"2023041909010512700_ocad008-B74","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.jhep.2017.03.021","article-title":"Clinical practice guidelines on the management of hepatitis B virus infection","volume":"67","author":"European Association for the Study of the Liver","year":"2017","journal-title":"J Hepatol"},{"issue":"9","key":"2023041909010512700_ocad008-B75","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1111\/liv.13142","article-title":"Incidence of hepatocellular carcinoma in untreated subjects with chronic hepatitis B: a systematic review and meta-analysis","volume":"36","author":"Raffetti","year":"2016","journal-title":"Liver Int"},{"issue":"6","key":"2023041909010512700_ocad008-B76","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1111\/jvh.13077","article-title":"Diabetes poses a higher risk of hepatocellular carcinoma and mortality in patients with chronic hepatitis B: a population-based cohort study","volume":"26","author":"Shyu","year":"2019","journal-title":"J Viral Hepat"},{"issue":"11","key":"2023041909010512700_ocad008-B77","doi-asserted-by":"crossref","first-page":"1629","DOI":"10.1038\/s41395-018-0247-9","article-title":"On-treatment improvement of MELD score reduces death and hepatic events in patients with hepatitis B-related cirrhosis","volume":"113","author":"Yip","year":"2018","journal-title":"Am J Gastroenterol"},{"issue":"3","key":"2023041909010512700_ocad008-B78","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1016\/j.jfma.2021.08.003","article-title":"Serum PIVKA-II and alpha-fetoprotein at virological remission predicts hepatocellular carcinoma in chronic hepatitis B related cirrhosis","volume":"121","author":"Su","year":"2022","journal-title":"J Formos Med Assoc"},{"issue":"9","key":"2023041909010512700_ocad008-B79","doi-asserted-by":"crossref","first-page":"998","DOI":"10.3390\/v12090998","article-title":"Advanced therapeutics, vaccinations, and precision medicine in the treatment and management of chronic hepatitis b viral infections; where are we and where are we going?","volume":"12","author":"Duraisamy","year":"2020","journal-title":"Viruses"},{"issue":"6","key":"2023041909010512700_ocad008-B80","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1007\/s12072-019-09989-6","article-title":"Finite nucleos (t) ide analog therapy in HBeAg-negative chronic hepatitis B: an emerging paradigm shift","volume":"13","author":"Liaw","year":"2019","journal-title":"Hepatol Int"},{"issue":"3","key":"2023041909010512700_ocad008-B81","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1002\/jcph.409","article-title":"A meta-analysis comparing the efficacy of entecavir and tenofovir for the treatment of chronic hepatitis B infection","volume":"55","author":"Zuo","year":"2015","journal-title":"J Clin Pharmacol"}],"container-title":["Journal of the American Medical Informatics Association"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/30\/5\/846\/49873077\/ocad008.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/30\/5\/846\/49873077\/ocad008.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,19]],"date-time":"2023-04-19T09:25:38Z","timestamp":1681896338000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jamia\/article\/30\/5\/846\/7040373"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,15]]},"references-count":81,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2023,2,15]]},"published-print":{"date-parts":[[2023,4,19]]}},"URL":"https:\/\/doi.org\/10.1093\/jamia\/ocad008","relation":{},"ISSN":["1067-5027","1527-974X"],"issn-type":[{"value":"1067-5027","type":"print"},{"value":"1527-974X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,5,1]]},"published":{"date-parts":[[2023,2,15]]}}}