{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,2,9]],"date-time":"2024-02-09T11:58:24Z","timestamp":1707479904918},"reference-count":15,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"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":["IT Prof."],"published-print":{"date-parts":[[2019,9,1]]},"DOI":"10.1109\/mitp.2019.2931415","type":"journal-article","created":{"date-parts":[[2019,9,11]],"date-time":"2019-09-11T19:53:41Z","timestamp":1568231621000},"page":"71-77","source":"Crossref","is-referenced-by-count":5,"title":["White Learning: A White-Box Data Fusion Machine Learning Framework for Extreme and Fast Automated Cancer Diagnosis"],"prefix":"10.1109","volume":"21","author":[{"given":"Tengyue","family":"Li","sequence":"first","affiliation":[{"name":"University of Macau"}]},{"given":"Simon","family":"Fong","sequence":"additional","affiliation":[{"name":"University of Macau"}]},{"given":"Lian-Sheng","family":"Liu","sequence":"additional","affiliation":[{"name":"Hospital of Guangzhou University of TCM"}]},{"given":"Xin-She","family":"Yang","sequence":"additional","affiliation":[{"name":"Middlesex University"}]},{"given":"Xingshi","family":"He","sequence":"additional","affiliation":[{"name":"Xi'an Polytechnic University"}]},{"given":"Jinan","family":"Fiaidhi","sequence":"additional","affiliation":[{"name":"Lakehead University"}]},{"given":"Sabah","family":"Mohammed","sequence":"additional","affiliation":[{"name":"Lakehead University"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1109\/ICPR.2002.1048418","article-title":"Bayesian networks as ensemble of classifiers","author":"garg","year":"2002","journal-title":"Object recognition supported by user interaction for service robots ICPR"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.09.024"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.1007\/s12652-018-0685-7","article-title":"Predicting unusual energy consumption events from smart home sensor network by data stream mining with misclassified recall","volume":"v9","author":"fong","year":"2018","journal-title":"J Ambient Intell Humanized Comput"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/srep43167"},{"key":"ref14","year":"2019"},{"key":"ref15","year":"1995"},{"key":"ref4","first-page":"1","article-title":"Constructing deep neural networks by Bayesian network structure learning","author":"rohekar","year":"0","journal-title":"Proc 32nd Conf Neural Inf Process Syst"},{"key":"ref3","first-page":"1","article-title":"Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity","author":"fruehwirt","year":"2019","journal-title":"Proc Conf Neural Inf Process Syst Mach Learn Health Workshop"},{"key":"ref6","article-title":"Building interpretable models: From Bayesian networks to neural networks","author":"krakovna","year":"2016"},{"key":"ref5","first-page":"916","article-title":"Bayesian deep convolution belief networks for subjectivity detection","author":"chaturvedi","year":"2016","journal-title":"Proc Workshops IEEE Int Conf Data Mining"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/S0933-3657(03)00053-8","article-title":"Bayesian applications of belief networks and multilayer perceptrons for ovarian tumor classification with rejection","volume":"29","author":"antal","year":"2003","journal-title":"Artif Intell Med"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.4258\/jksmi.2009.15.1.49"},{"key":"ref2","article-title":"Bayesian methods for neural networks","author":"de freitas","year":"2009"},{"key":"ref1","first-page":"598","article-title":"A practical Monte Carlo implementation of Bayesian learning","author":"rasmussen","year":"1995","journal-title":"Proc 8th Int Conf Neural Inf Process Syst"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2016.7727837"}],"container-title":["IT Professional"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6294\/8832288\/08832275.pdf?arnumber=8832275","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:41:30Z","timestamp":1657744890000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8832275\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,1]]},"references-count":15,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/mitp.2019.2931415","relation":{},"ISSN":["1520-9202","1941-045X"],"issn-type":[{"value":"1520-9202","type":"print"},{"value":"1941-045X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,1]]}}}