{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T02:48:08Z","timestamp":1730342888416,"version":"3.28.0"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,9,13]],"date-time":"2021-09-13T00:00:00Z","timestamp":1631491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,9,13]],"date-time":"2021-09-13T00:00:00Z","timestamp":1631491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,13]]},"DOI":"10.23919\/cinc53138.2021.9662749","type":"proceedings-article","created":{"date-parts":[[2022,1,10]],"date-time":"2022-01-10T21:12:26Z","timestamp":1641849146000},"page":"1-4","source":"Crossref","is-referenced-by-count":0,"title":["Demystifying Heart Failure with Mid-Range Ejection Fraction Using Machine Learning"],"prefix":"10.23919","author":[{"given":"Achal","family":"Dixit","sequence":"first","affiliation":[]},{"given":"Soumi","family":"Chattopadhyay","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1002\/ejhf.1091"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jchf.2016.02.017"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2012.11.008"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.4137\/CMC.S18746"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2016.06.029"},{"key":"ref15","article-title":"Hospitalized patients with heart failure: integrating electronic healthcare records and external outcome data (version 1.1)","author":"zhang","year":"2020","journal-title":"PhysioNet"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/B978-032304841-5.50025-X"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2008.4633969"},{"key":"ref18","first-page":"2","volume":"12","author":"bouchefry","year":"2020","journal-title":"Knowledge Discovery in Big Data from Astronomy and Earth Observation"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-1803-1_5"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1002\/ejhf.1116"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"2129","DOI":"10.1093\/eurheartj\/ehw128","article-title":"2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC","volume":"37","author":"ponikowski","year":"2016","journal-title":"Eur Heart J"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.1093\/eurheartj\/ehs104","article-title":"ESC Committee for Practice Guidelines. ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2012: the task force for the diagnosis and treatment of acute and chronic heart failure 2012 of the European Society of Cardiology & Heart Failure Association (HFA) of the ESC","volume":"33","author":"mcmurray","year":"2012","journal-title":"Eur Heart J"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"1e","DOI":"10.1016\/j.cardfail.2010.04.004","article-title":"HFSA 2010 comprehensive heart failure practice guideline","volume":"16","author":"lindenfeld","year":"2010","journal-title":"J Card Fail"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/ejhf.807"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1111\/echo.12331"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1093\/eurheartj\/ehz859","article-title":"European society of cardiology: cardiovascular disease statistics 2019","volume":"41","author":"timmis","year":"2020","journal-title":"European Heart Journal"},{"key":"ref1","article-title":"On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee “A report from the American Heart Association","author":"virani","year":"0","journal-title":"Heart Disease and Stroke Statistics-2020 Update"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ahj.2014.07.008"},{"key":"ref20","first-page":"2825","article-title":"Scikit-learn: machine learning in python","volume":"12","author":"pedregosa","year":"2011","journal-title":"JMLR"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2017.2654504"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/0925-2312(91)90023-5"},{"key":"ref24","article-title":"Consistency-Based Semi-supervised Active Learning: Towards Minimizing Labeling Cost","volume":"12355","author":"gao","year":"0","journal-title":"Computer Vision – ECCV 2020"},{"key":"ref23","article-title":"Cold-start active learning with robust ordinal matrix factorization","author":"houlsby","year":"0","journal-title":"ICML"}],"event":{"name":"2021 Computing in Cardiology (CinC)","start":{"date-parts":[[2021,9,13]]},"location":"Brno, Czech Republic","end":{"date-parts":[[2021,9,15]]}},"container-title":["2021 Computing in Cardiology (CinC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9662654\/9662645\/09662749.pdf?arnumber=9662749","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,18]],"date-time":"2022-04-18T20:29:57Z","timestamp":1650313797000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9662749\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,13]]},"references-count":24,"URL":"https:\/\/doi.org\/10.23919\/cinc53138.2021.9662749","relation":{},"subject":[],"published":{"date-parts":[[2021,9,13]]}}}