{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T14:15:05Z","timestamp":1779891305287,"version":"3.53.1"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.2967075","type":"journal-article","created":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T21:06:26Z","timestamp":1579295186000},"page":"16350-16361","source":"Crossref","is-referenced-by-count":28,"title":["Medical Multimedia Big Data Analysis Modeling Based on DBN Algorithm"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7225-1541","authenticated-orcid":false,"given":"Ying","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1080\/10798587.2016.1267251"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpj.2016.11.334"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s10033-017-0190-5"},{"key":"ref13","first-page":"229","article-title":"Active deep learning-based annotation of electroencephalography reports for cohort identification","volume":"2017","author":"maldonado","year":"2017","journal-title":"AMIA Summits Transl Sci Proc"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.4018\/IJMDEM.2017010101"},{"key":"ref15","first-page":"1","article-title":"Detecting anomalous emotion through big data from social networks based on a DBN method","volume":"2018","author":"xiao","year":"2018","journal-title":"Multimedia Tools Appl"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2696365"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2018.2825987"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/MITP.2017.52"},{"key":"ref19","first-page":"361","article-title":"DBN predictions of survival based on MRI in amyotrophic lateral sclerosis","volume":"13","author":"burgh","year":"2017","journal-title":"Clin Neuro"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-018-5331-3"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.26599\/BDMA.2018.9020020"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-017-4591-3"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.08.005"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-018-0636-4"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2018.01.010"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1166\/asl.2017.8643"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"12394","DOI":"10.1111\/exsy.12394","article-title":"Big data solar power forecasting based on DBN and multiple data sources","volume":"36","author":"torres","year":"2019","journal-title":"Expert Syst"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1142\/S1793351X17400050"},{"key":"ref2","first-page":"1","article-title":"Risk management of commodity trade business based on DBN and parallel processing of visual multimedia big data","volume":"2019","author":"zhang","year":"2019","journal-title":"Multimedia Tools Appl"},{"key":"ref9","first-page":"90","article-title":"Computer-aided lung cancer diagnosis approaches based on DBN","volume":"30","author":"zhang","year":"2018","journal-title":"J Comput -Aided Des Comput Graph"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2017.11.032"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2668840"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-018-1136-9"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"211","DOI":"10.26599\/BDMA.2018.9020019","article-title":"A novel deep hybrid recommender system based on auto-encoder with neural collaborative filtering","volume":"1","author":"yu","year":"2018","journal-title":"Big data mining and analytics"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"2220","DOI":"10.3390\/s18072220","article-title":"A deep CNN-LSTM Model for Particulate Matter (PM2.5) forecasting in smart cities","volume":"18","author":"huang","year":"2018","journal-title":"SENSORS"},{"key":"ref23","first-page":"1","article-title":"Deep learning and its applications to machine health monitoring: A survey","volume":"14","author":"rui","year":"2015","journal-title":"Journal of latex class files"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-019-07853-1"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2905537"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/08962052.pdf?arnumber=8962052","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T19:55:33Z","timestamp":1643313333000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8962052\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/access.2020.2967075","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}