{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T20:05:10Z","timestamp":1745352310448},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2021,12]]},"DOI":"10.1016\/j.knosys.2021.107534","type":"journal-article","created":{"date-parts":[[2021,9,27]],"date-time":"2021-09-27T11:00:56Z","timestamp":1632740456000},"page":"107534","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":15,"special_numbering":"C","title":["MeSIN: Multilevel selective and interactive network for medication recommendation"],"prefix":"10.1016","volume":"233","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-6529-1609","authenticated-orcid":false,"given":"Yang","family":"An","sequence":"first","affiliation":[]},{"given":"Liang","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Mao","family":"You","sequence":"additional","affiliation":[]},{"given":"Xueqing","family":"Tian","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-4094-7499","authenticated-orcid":false,"given":"Bo","family":"Jin","sequence":"additional","affiliation":[]},{"given":"Xiaopeng","family":"Wei","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.knosys.2021.107534_b1","doi-asserted-by":"crossref","first-page":"1213","DOI":"10.1038\/nbt.3052","article-title":"A community computational challenge to predict the activity of pairs of compounds","volume":"32","author":"Bansal","year":"2014","journal-title":"Nature Biotechnol."},{"key":"10.1016\/j.knosys.2021.107534_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.metabol.2020.154242","article-title":"Use of incretin-based medications: what do current international recommendations suggest with respect to GLP-1 receptor agonists and DPP-4 inhibitors?","author":"Davies","year":"2020","journal-title":"Metab.: Clin. Exp."},{"key":"10.1016\/j.knosys.2021.107534_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.yebeh.2021.107804","article-title":"Appropriate use of generic and branded antiseizure medications in epilepsy: Updated recommendations from the Italian league against epilepsy (LICE)","volume":"116","author":"Roberti","year":"2021","journal-title":"Epilepsy Behav."},{"key":"10.1016\/j.knosys.2021.107534_b4","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1001\/jama.2018.11100","article-title":"Deep learning-a technology with the potential to transform health care","volume":"320 11","author":"Hinton","year":"2018","journal-title":"JAMA"},{"key":"10.1016\/j.knosys.2021.107534_b5","series-title":"AAAI","first-page":"606","article-title":"Learning the graphical structure of electronic health records with graph convolutional transformer","author":"Choi","year":"2020"},{"key":"10.1016\/j.knosys.2021.107534_b6","series-title":"AAAI","first-page":"1126","article-title":"Gamenet: Graph augmented memory networks for recommending medication combination","author":"Shang","year":"2019"},{"key":"10.1016\/j.knosys.2021.107534_b7","series-title":"Proceedings of the 23th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"1315","article-title":"Leap: Learning to prescribe effective and safe treatment combinations for multimorbidity","author":"Zhang","year":"2017"},{"key":"10.1016\/j.knosys.2021.107534_b8","series-title":"CIKM","first-page":"1623","article-title":"Order-free medicine combination prediction with graph convolutional reinforcement learning","author":"Wang","year":"2019"},{"key":"10.1016\/j.knosys.2021.107534_b9","series-title":"SIGKDD","first-page":"1637","article-title":"Dual memory neural computer for asynchronous two-view sequential learning","author":"Le","year":"2018"},{"key":"10.1016\/j.knosys.2021.107534_b10","first-page":"125","article-title":"Attention and memory-augmented networks for dual-view sequential learning","author":"He","year":"2020","journal-title":"SIGKDD"},{"key":"10.1016\/j.knosys.2021.107534_b11","series-title":"SIGKDD","first-page":"1608","article-title":"A treatment engine by predicting next-period prescriptions","author":"Jin","year":"2018"},{"key":"10.1016\/j.knosys.2021.107534_b12","doi-asserted-by":"crossref","DOI":"10.1016\/j.jbi.2020.103502","article-title":"Rahm: Relation augmented hierarchical multi-task learning framework for reasonable medication stocking","volume":"108","author":"An","year":"2020","journal-title":"J. Biomed. Inform."},{"key":"10.1016\/j.knosys.2021.107534_b13","series-title":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","first-page":"1753","article-title":"Lsan: Modeling long-term dependencies and short-term correlations with hierarchical attention for risk prediction","author":"Ye","year":"2020"},{"key":"10.1016\/j.knosys.2021.107534_b14","doi-asserted-by":"crossref","DOI":"10.14704\/WEB\/V16I1\/a178","article-title":"Health recommender system in social networks: A case of facebook","volume":"16","author":"Forouzandeh","year":"2019","journal-title":"Webology"},{"key":"10.1016\/j.knosys.2021.107534_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijhcs.2021.102610","article-title":"Automated and personalized nutrition health assessment, recommendation, and progress evaluation using fuzzy reasoning","volume":"151","author":"Salloum","year":"2021","journal-title":"Int. J. Hum.-Comput. Stud."},{"key":"10.1016\/j.knosys.2021.107534_b16","doi-asserted-by":"crossref","first-page":"1419","DOI":"10.1093\/jamia\/ocy068","article-title":"Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review","volume":"25","author":"Xiao","year":"2018","journal-title":"J. Am. Med. Inform. Assoc. : JAMIA"},{"key":"10.1016\/j.knosys.2021.107534_b17","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/MCSE.2018.2875321","article-title":"Addressing the cold-start problem using data mining techniques and improving recommender systems by cuckoo algorithm: A case study of facebook","volume":"22","author":"Forouzandeh","year":"2020","journal-title":"Comput. Sci. Eng."},{"key":"10.1016\/j.knosys.2021.107534_b18","doi-asserted-by":"crossref","first-page":"7805","DOI":"10.1007\/s11042-020-09949-5","article-title":"Presentation of a recommender system with ensemble learning and graph embedding: a case on MovieLens","volume":"80","author":"Forouzandeh","year":"2021","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.knosys.2021.107534_b19","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1007\/s40747-020-00212-w","article-title":"Artificial intelligence in recommender systems","volume":"7","author":"Zhang","year":"2020","journal-title":"Complex Intell. Syst."},{"issue":"2","key":"10.1016\/j.knosys.2021.107534_b20","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.cmpb.2014.06.019","article-title":"A smart medication recommendation model for the electronic prescription","volume":"117","author":"Syed-Abdul","year":"2014","journal-title":"Comput. Methods Programs Biomed.","ISSN":"http:\/\/id.crossref.org\/issn\/0169-2607","issn-type":"print"},{"key":"10.1016\/j.knosys.2021.107534_b21","series-title":"SIGKDD","first-page":"1315","article-title":"Leap: Learning to prescribe effective and safe treatment combinations for multimorbidity","author":"Zhang","year":"2017"},{"key":"10.1016\/j.knosys.2021.107534_b22","series-title":"SIGKDD","first-page":"1608","article-title":"A treatment engine by predicting next-period prescriptions","author":"Jin","year":"2018"},{"key":"10.1016\/j.knosys.2021.107534_b23","series-title":"IJCAI","first-page":"5953","article-title":"Pre-training of graph augmented transformers for medication recommendation","author":"Shang","year":"2019"},{"key":"10.1016\/j.knosys.2021.107534_b24","series-title":"ACL","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2019"},{"key":"10.1016\/j.knosys.2021.107534_b25","series-title":"ACL","first-page":"4782","article-title":"Learning to deceive with attention-based explanations","author":"Pruthi","year":"2020"},{"key":"10.1016\/j.knosys.2021.107534_b26","doi-asserted-by":"crossref","first-page":"3016","DOI":"10.1109\/TCSVT.2018.2872503","article-title":"Sharp attention network via adaptive sampling for person re-identification","volume":"29","author":"Shen","year":"2019","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.knosys.2021.107534_b27","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1109\/TCSVT.2020.2978115","article-title":"Attentional kernel encoding networks for fine-grained visual categorization","volume":"31","author":"Hu","year":"2021","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.knosys.2021.107534_b28","series-title":"Proceedings of the 23th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"787","article-title":"Gram: Graph-based attention model for healthcare representation learning","author":"Choi","year":"2017"},{"key":"10.1016\/j.knosys.2021.107534_b29","series-title":"CIKM","first-page":"743","article-title":"KAME: Knowledge-based attention model for diagnosis prediction in healthcare","author":"Ma","year":"2018"},{"key":"10.1016\/j.knosys.2021.107534_b30","series-title":"Advances in Neural Information Processing Systems 29","first-page":"3504","article-title":"Retain: An interpretable predictive model for healthcare using reverse time attention mechanism","author":"Choi","year":"2016"},{"key":"10.1016\/j.knosys.2021.107534_b31","series-title":"Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"1903","article-title":"Dipole: Diagnosis prediction in healthcare via attention-based bidirectional recurrent neural networks","author":"Ma","year":"2017"},{"key":"10.1016\/j.knosys.2021.107534_b32","series-title":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"43","article-title":"Interpretable representation learning for healthcare via capturing disease progression through time","author":"Bai","year":"2018"},{"key":"10.1016\/j.knosys.2021.107534_b33","series-title":"NIPS","first-page":"5998","article-title":"Attention is all you need","author":"Vaswani","year":"2017"},{"key":"10.1016\/j.knosys.2021.107534_b34","series-title":"Advances in Neural Information Processing Systems 31","first-page":"4547","article-title":"Mime: Multilevel medical embedding of electronic health records for predictive healthcare","author":"Choi","year":"2018"},{"key":"10.1016\/j.knosys.2021.107534_b35","series-title":"IJCAI","first-page":"5937","article-title":"Mnn: Multimodal attentional neural networks for diagnosis prediction","author":"Qiao","year":"2019"},{"key":"10.1016\/j.knosys.2021.107534_b36","series-title":"IJCAI","first-page":"4369","article-title":"Attain: Attention-based time-aware LSTM networks for disease progression modeling","author":"Zhang","year":"2019"},{"key":"10.1016\/j.knosys.2021.107534_b37","series-title":"AAAI","first-page":"557","article-title":"Doctor2Vec: Dynamic doctor representation learning for clinical trial recruitment","author":"Biswal","year":"2020"},{"key":"10.1016\/j.knosys.2021.107534_b38","series-title":"WWW","first-page":"1029","article-title":"DeepEnroll: Patient-trial matching with deep embedding and entailment prediction","author":"Zhang","year":"2020"},{"key":"10.1016\/j.knosys.2021.107534_b39","series-title":"Proceedings of the 23th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"65","article-title":"Patient subtyping via time-aware LSTM networks","author":"Baytas","year":"2017"},{"key":"10.1016\/j.knosys.2021.107534_b40","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34","first-page":"833","article-title":"Concare: Personalized clinical feature embedding via capturing the healthcare context","author":"Ma","year":"2020"},{"key":"10.1016\/j.knosys.2021.107534_b41","series-title":"Neurocomputing","first-page":"227","article-title":"Probabilistic interpretation of feedforward classification network outputs, with relationships to statistical pattern recognition","author":"Bridle","year":"1990"},{"key":"10.1016\/j.knosys.2021.107534_b42","series-title":"ACL","first-page":"1504","article-title":"Sparse sequence-to-sequence models","author":"Peters","year":"2019"},{"issue":"8","key":"10.1016\/j.knosys.2021.107534_b43","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"10.1016\/j.knosys.2021.107534_b44","doi-asserted-by":"crossref","DOI":"10.1038\/sdata.2016.35","article-title":"Mimic-III, a freely accessible critical care database","author":"Johnson","year":"2016","journal-title":"Sci. Data"},{"key":"10.1016\/j.knosys.2021.107534_b45","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1016\/j.amjcard.2005.04.029","article-title":"Effect of statin use within the first 24 hours of admission for acute myocardial infarction on early morbidity and mortality","volume":"96","author":"Fonarow","year":"2005","journal-title":"Am. J. Cardiol."},{"key":"10.1016\/j.knosys.2021.107534_b46","doi-asserted-by":"crossref","DOI":"10.1038\/s41597-019-0103-9","article-title":"Multitask learning and benchmarking with clinical time series data","volume":"6","author":"Harutyunyan","year":"2019","journal-title":"Sci. Data"},{"key":"10.1016\/j.knosys.2021.107534_b47","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/s13748-012-0030-x","article-title":"Binary relevance efficacy for multilabel classification","volume":"1","author":"Luaces","year":"2012","journal-title":"Prog. Artif. Intell."},{"key":"10.1016\/j.knosys.2021.107534_b48","doi-asserted-by":"crossref","DOI":"10.3389\/fnagi.2017.00077","article-title":"A Bayesian model for the prediction and early diagnosis of Alzheimer\u2019s disease","volume":"9","author":"Alexiou","year":"2017","journal-title":"Front. Aging Neurosci."},{"key":"10.1016\/j.knosys.2021.107534_b49","series-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705121007966?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705121007966?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T17:02:00Z","timestamp":1714237320000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705121007966"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12]]},"references-count":49,"alternative-id":["S0950705121007966"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2021.107534","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2021,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"MeSIN: Multilevel selective and interactive network for medication recommendation","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2021.107534","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"107534"}}