{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T09:11:15Z","timestamp":1742980275993,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030862701"},{"type":"electronic","value":"9783030862718"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-86271-8_48","type":"book-chapter","created":{"date-parts":[[2021,9,14]],"date-time":"2021-09-14T23:08:06Z","timestamp":1631660886000},"page":"576-587","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Edge AI for Covid-19 Detection Using Coughing"],"prefix":"10.1007","author":[{"given":"J. A.","family":"Rincon","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V.","family":"Julian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"C.","family":"Carrascosa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,15]]},"reference":[{"issue":"4","key":"48_CR1","doi-asserted-by":"publisher","first-page":"e2112","DOI":"10.1002\/rmv.2112","volume":"30","author":"A Pormohammad","year":"2020","unstructured":"Pormohammad, A., et al.: Comparison of confirmed COVID-19 with SARS and MERS cases-clinical characteristics, laboratory findings, radiographic signs and outcomes: a systematic review and meta-analysis. Rev. Med. Virol. 30(4), e2112 (2020)","journal-title":"Rev. Med. Virol."},{"key":"48_CR2","doi-asserted-by":"publisher","unstructured":"Chugh, G., Kumar, S., Singh, N.: Survey on machine learning and deep learning applications in breast cancer diagnosis. Cogn. Comput. 1\u201320 (2021). https:\/\/doi.org\/10.1007\/s12559-020-09813-6","DOI":"10.1007\/s12559-020-09813-6"},{"issue":"3","key":"48_CR3","doi-asserted-by":"publisher","first-page":"846","DOI":"10.1166\/jmihi.2021.3309","volume":"11","author":"H Riaz","year":"2021","unstructured":"Riaz, H., Park, J., Kim, P.H., Kim, J.: Retinal healthcare diagnosis approaches with deep learning techniques. J. Med. Imaging Health Inform. 11(3), 846\u2013855 (2021)","journal-title":"J. Med. Imaging Health Inform."},{"key":"48_CR4","doi-asserted-by":"crossref","unstructured":"Muhammad, Y., Alshehri, M.D., Alenazy, W.M., Vinh Hoang, T., Alturki, R.: Identification of pneumonia disease applying an intelligent computational framework based on deep learning and machine learning techniques. Mob. Inf. Syst. 2021 (2021)","DOI":"10.1155\/2021\/9989237"},{"key":"48_CR5","unstructured":"Deshpande, G., Schuller, B.: An overview on audio, signal, speech, & language processing for COVID-19. arXiv preprint arXiv:2005.08579 (2020)"},{"key":"48_CR6","doi-asserted-by":"crossref","unstructured":"Belkacem, A.N., Ouhbi, S., Lakas, A., Benkhelifa, E., Chen, C.: End-to-end AI-based point-of-care diagnosis system for classifying respiratory illnesses and early detection of COVID-19. arXiv e-prints, arXiv-2006 (2020)","DOI":"10.3389\/fmed.2021.585578"},{"key":"48_CR7","doi-asserted-by":"crossref","unstructured":"Schuller, B.W., Schuller, D.M., Qian, K., Liu, J., Zheng, H., Li, X.: COVID-19 and computer audition: an overview on what speech & sound analysis could contribute in the SARS-CoV-2 corona crisis. arXiv preprint arXiv:2003.11117 (2020)","DOI":"10.3389\/fdgth.2021.564906"},{"issue":"5","key":"48_CR8","doi-asserted-by":"publisher","first-page":"484","DOI":"10.3390\/mi11050484","volume":"11","author":"SA Zawawi","year":"2020","unstructured":"Zawawi, S.A., Hamzah, A.A., Majlis, B.Y., Mohd-Yasin, F.: A review of mems capacitive microphones. Micromachines 11(5), 484 (2020)","journal-title":"Micromachines"},{"key":"48_CR9","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1007\/978-3-030-45691-7_4","volume-title":"Trends and Innovations in Information Systems and Technologies","author":"W Li","year":"2020","unstructured":"Li, W., Liewig, M.: A survey of AI accelerators for edge environment. In: Rocha, \u00c1., Adeli, H., Reis, L.P., Costanzo, S., Orovic, I., Moreira, F. (eds.) WorldCIST 2020. AISC, vol. 1160, pp. 35\u201344. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-45691-7_4"},{"key":"48_CR10","doi-asserted-by":"publisher","first-page":"101079","DOI":"10.1109\/ACCESS.2020.2997831","volume":"8","author":"L Sun","year":"2020","unstructured":"Sun, L., Jiang, X., Ren, H., Guo, Y.: Edge-cloud computing and artificial intelligence in internet of medical things: architecture, technology and application. IEEE Access 8, 101079\u2013101092 (2020)","journal-title":"IEEE Access"},{"key":"48_CR11","doi-asserted-by":"crossref","unstructured":"Rahman, M.A., Hossain, M.S.: An internet of medical things-enabled edge computing framework for tackling COVID-19. IEEE Internet Things J. (2021)","DOI":"10.1109\/JIOT.2021.3051080"},{"key":"48_CR12","doi-asserted-by":"publisher","first-page":"101830","DOI":"10.1016\/j.sysarc.2020.101830","volume":"108","author":"A Sufian","year":"2020","unstructured":"Sufian, A., Ghosh, A., Sadiq, A.S., Smarandache, F.: A survey on deep transfer learning to edge computing for mitigating the COVID-19 pandemic. J. Syst. Arch. 108, 101830 (2020)","journal-title":"J. Syst. Arch."},{"issue":"1","key":"48_CR13","doi-asserted-by":"publisher","first-page":"17","DOI":"10.3390\/designs5010017","volume":"5","author":"M Ahsan","year":"2021","unstructured":"Ahsan, M., Based, M., Haider, J., Rodrigues, E.M.G., et al.: Smart monitoring and controlling of appliances using LoRa based IoT system. Designs 5(1), 17 (2021)","journal-title":"Designs"},{"issue":"6","key":"48_CR14","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.1109\/TLA.2021.9451246","volume":"19","author":"F Rodriguez","year":"2021","unstructured":"Rodriguez, F., et al.: IoMT: Rinku\u2019s clinical kit applied to collect information related to COVID-19 through medical sensors. IEEE Latin Am. Trans. 19(6), 1002\u20131009 (2021)","journal-title":"IEEE Latin Am. Trans."},{"key":"48_CR15","doi-asserted-by":"crossref","unstructured":"Fakhry, A., Jiang, X., Xiao, J., Chaudhari, G., Han, A., Khanzada, A.: Virufy: a multi-branch deep learning network for automated detection of COVID-19. arXiv preprint arXiv:2103.01806 (2021)","DOI":"10.21437\/Interspeech.2021-378"},{"key":"48_CR16","unstructured":"Denoyer, L., Gallinari, P.: Deep sequential neural network. arXiv preprint arXiv:1410.0510 (2014)"},{"key":"48_CR17","doi-asserted-by":"crossref","unstructured":"Feng, K., He, F., Steinmann, J., Demirkiran, I.: Deep-learning based approach to identify Covid-19. In: SoutheastCon 2021, pp. 1\u20134. IEEE (2021)","DOI":"10.1109\/SoutheastCon45413.2021.9401826"},{"key":"48_CR18","unstructured":"Kumar, L.K., Alphonse, P.J.A.: Automatic diagnosis of COVID-19 disease using deep convolutional neural network with multi-feature channel from respiratory sound data: cough, voice, and breath. Alex. Eng. J. (2021)"}],"container-title":["Lecture Notes in Computer Science","Hybrid Artificial Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-86271-8_48","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T19:36:51Z","timestamp":1710358611000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-86271-8_48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030862701","9783030862718"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-86271-8_48","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"15 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HAIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Hybrid Artificial Intelligence Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bilbao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hais2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2021.haisconference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"81","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"44","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"11","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"54% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2-3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}