{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T16:01:50Z","timestamp":1773331310527,"version":"3.50.1"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-009"},{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-001"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,12,10]]},"DOI":"10.1109\/bigdata50022.2020.9378276","type":"proceedings-article","created":{"date-parts":[[2021,3,19]],"date-time":"2021-03-19T21:10:21Z","timestamp":1616188221000},"page":"1374-1379","source":"Crossref","is-referenced-by-count":14,"title":["r-LSTM: Time Series Forecasting for COVID-19 Confirmed Cases with LSTMbased Framework"],"prefix":"10.1109","author":[{"given":"Mohammad","family":"Masum","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hossain","family":"Shahriar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hisham M.","family":"Haddad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Md. Shafiul","family":"Alam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2020.109853"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.tmaid.2020.101742"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s00477-020-01827-8"},{"key":"ref13","article-title":"Day level forecasting for Coronavirus Disease (COVID-19) spread: analysis, modeling and recommendations","author":"elmousalami","year":"2020"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1002\/for.3980020104"},{"key":"ref15","article-title":"An overview and comparative analysis of recurrent neural networks for short term load forecasting","author":"bianchi","year":"2017"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2020.109864"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/2470171"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-94968-0_25"},{"key":"ref19","article-title":"A Comparative Analysis of Forecasting Financial Time Series Using ARIMA","author":"siami-namini","year":"2019","journal-title":"LSTM and BiLSTM"},{"key":"ref4","article-title":"Day level forecasting for Coronavirus Disease (COVID-19) spread: analysis, modeling and recommendations","author":"elmousalami","year":"2020"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2981506"},{"key":"ref6","year":"0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijsu.2020.02.034"},{"key":"ref8","article-title":"Coronavirus (COVID-19): ARIMA based time-series analysis to forecast near future","author":"tandon","year":"2020"},{"key":"ref7","year":"0"},{"key":"ref2","article-title":"Re-analysis of SARS-CoV-2 infected host cell proteomics time-course data by impact pathway analysis and network analysis","author":"ortea","year":"2020","journal-title":"A potential link with inflammatory response"},{"key":"ref1","author":"estrada","year":"2020","journal-title":"Topological Analysis of SARS CoV-2 Main Protease"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0231236"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2020.109850"},{"key":"ref22","year":"0"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.460"}],"event":{"name":"2020 IEEE International Conference on Big Data (Big Data)","location":"Atlanta, GA, USA","start":{"date-parts":[[2020,12,10]]},"end":{"date-parts":[[2020,12,13]]}},"container-title":["2020 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9377717\/9377728\/09378276.pdf?arnumber=9378276","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:45:33Z","timestamp":1656344733000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9378276\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,10]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/bigdata50022.2020.9378276","relation":{},"subject":[],"published":{"date-parts":[[2020,12,10]]}}}