{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T03:14:08Z","timestamp":1743131648935,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031424298"},{"type":"electronic","value":"9783031424304"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-42430-4_40","type":"book-chapter","created":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T15:03:54Z","timestamp":1695913434000},"page":"487-497","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Improvement of the Process of Diagnosing Patient\u2019s Condition via Computer Tomography Lung Scans Using Neural Networks"],"prefix":"10.1007","author":[{"given":"Marcin","family":"Nahajowski","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7764-1303","authenticated-orcid":false,"given":"Michal","family":"Kedziora","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2160-7077","authenticated-orcid":false,"given":"Ireneusz","family":"Jozwiak","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,29]]},"reference":[{"key":"40_CR1","first-page":"9","volume":"9","author":"ZZ Abidin","year":"2018","unstructured":"Abidin, Z.Z., et al.: Crypt-tag authentication in NFC implementation for medicine data management. Int. J. Adv. Comput. Sci. Appl. 9, 9 (2018)","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"issue":"2","key":"40_CR2","doi-asserted-by":"publisher","first-page":"56","DOI":"10.3390\/healthcare7020056","volume":"7","author":"CC Agbo","year":"2019","unstructured":"Agbo, C.C., Mahmoud, Q.H., Eklund, J.M.: Blockchain technology in healthcare: a systematic review. Healthcare 7(2), 56 (2019)","journal-title":"Healthcare"},{"key":"40_CR3","doi-asserted-by":"publisher","first-page":"101734","DOI":"10.1016\/j.bspc.2019.101734","volume":"56","author":"E Ba\u015faran","year":"2020","unstructured":"Ba\u015faran, E., C\u00f6mert, Z., \u00c7elik, Y.: Convolutional neural network approach for automatic tympanic membrane detection and classification. Biomed. Signal Process. Control 56, 101734 (2020)","journal-title":"Biomed. Signal Process. Control"},{"key":"40_CR4","doi-asserted-by":"publisher","first-page":"143","DOI":"10.3399\/bjgp18X695213","volume":"68","author":"VH Buch","year":"2018","unstructured":"Buch, V.H., Ahmed, I., Maruthappu, M.: Artificial intelligence in medicine: current trends and future possibilities. Br. J. Gen. Pract. 68, 143\u2013144 (2018)","journal-title":"Br. J. Gen. Pract."},{"key":"40_CR5","doi-asserted-by":"crossref","unstructured":"Davenport, T., Kalakota, R.: The potential for artificial intelligence in healthcare. Future Healthc. J. 6(2), 94\u201398 (2019). 403\u2013406","DOI":"10.7861\/futurehosp.6-2-94"},{"key":"40_CR6","doi-asserted-by":"crossref","unstructured":"Debnath, S., et al.: Machine learning to assist clinical decision-making during the COVID-19 pandemic. Bioelectron. Med. 6(14), 14 (2020). The Northwell COVID-19 Research Consortium","DOI":"10.1186\/s42234-020-00050-8"},{"key":"40_CR7","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Deep convolutional neural networks for image classification: a comprehensive review. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, vol. 29, no 9, pp. 248\u2013255 (2017)"},{"issue":"4","key":"40_CR8","doi-asserted-by":"publisher","first-page":"e27468","DOI":"10.2196\/27468","volume":"23","author":"M Ghaderzadeh","year":"2021","unstructured":"Ghaderzadeh, M., Asadi, F., Jafari, J.R., Bashash, D., Abolghasemi, H., Aria, M.: Deep convolutional neural network-based computer-aided detection system for COVID-19 using multiple lung scans: design and implementation study. J. Med. Internet Res. 23(4), e27468 (2021)","journal-title":"J. Med. Internet Res."},{"key":"40_CR9","doi-asserted-by":"crossref","unstructured":"Gruda, M., Kedziora, M.: Analyzing and improving tools for supporting fighting against COVID-19 based on prediction models and contact tracing. Bull. Polish Acad. Sci.: Tech. Sci. e137414\u2013e137414 (2021)","DOI":"10.24425\/bpasts.2021.137414"},{"key":"40_CR10","doi-asserted-by":"crossref","unstructured":"Yadav, Samir S.., Jadhav, Shivajirao M..: Deep convolutional neural network based medical image classification for disease diagnosis. J. Big Data 6(113) (2019)","DOI":"10.1186\/s40537-019-0276-2"},{"key":"40_CR11","doi-asserted-by":"crossref","unstructured":"Jin, C., et al.: Development and evaluation of an artificial intelligence system for COVID-19 diagnosis. Nat. Commun. 5088 (2020)","DOI":"10.1038\/s41467-020-18685-1"},{"issue":"4","key":"40_CR12","doi-asserted-by":"publisher","first-page":"462","DOI":"10.3390\/jcm8040462","volume":"8","author":"M Owais","year":"2019","unstructured":"Owais, M., Arsalan, M., Choi, J., Park, K.R.: Effective diagnosis and treatment through content-based medical image retrieval (CBMIR) by using artificial intelligence. J. Clin. Med. 8(4), 462 (2019)","journal-title":"J. Clin. Med."},{"key":"40_CR13","doi-asserted-by":"crossref","unstructured":"Ozturk, T., Talo, M., Yildirim, E.A., Baloglu, U.B., Yildirim, O., Acharya, U.: Automated detection of COVID-19 cases using deep neural networks with x-ray images. Comput. Biol. Med. 121 (2020)","DOI":"10.1016\/j.compbiomed.2020.103792"},{"key":"40_CR14","first-page":"103792","volume":"121","author":"F Piccialli","year":"2021","unstructured":"Piccialli, F., di Cola, V.S., Giampaolo, F., Cuomo, S.: The role of artificial intelligence in fighting the COVID-19 pandemic. Inf. Syst. Front. 121, 103792 (2021)","journal-title":"Inf. Syst. Front."},{"issue":"9","key":"40_CR15","doi-asserted-by":"publisher","first-page":"2352","DOI":"10.1162\/neco_a_00990","volume":"29","author":"W Rawat","year":"2017","unstructured":"Rawat, W., Wang, Z.: Deep convolutional neural networks for image classification: a comprehensive review. Neural Comput. 29(9), 2352\u20132449 (2017)","journal-title":"Neural Comput."},{"issue":"6","key":"40_CR16","doi-asserted-by":"publisher","first-page":"1311","DOI":"10.1007\/s12553-021-00601-2","volume":"11","author":"S Swayamsiddha","year":"2021","unstructured":"Swayamsiddha, S., Prashant, K., Shaw, D., Mohanty, C.: The prospective of artificial intelligence in COVID-19 pandemic. Health Technol. 11(6), 1311\u20131320 (2021). https:\/\/doi.org\/10.1007\/s12553-021-00601-2","journal-title":"Health Technol."},{"key":"40_CR17","doi-asserted-by":"publisher","first-page":"103805","DOI":"10.1016\/j.compbiomed.2020.103805","volume":"121","author":"M To\u011fa\u00e7ar","year":"2020","unstructured":"To\u011fa\u00e7ar, M., Ergen, B., C\u00f6mert, Z.: COVID-19 detection using deep learning models to exploit social mimic optimization and structured chest x-ray images using fuzzy color and stacking approaches. Comput. Biol. Med. 121, 103805 (2020)","journal-title":"Comput. Biol. Med."},{"key":"40_CR18","doi-asserted-by":"crossref","unstructured":"Ucar, F., Korkmaz, D.: COVIDiagnosis-Net: deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from x-ray images. Comput. Biol. Med. 140, 109761 (2020)","DOI":"10.1016\/j.mehy.2020.109761"},{"key":"40_CR19","unstructured":"Zhao, J., Zhang, Y., He, X., Xie, P.: COVID-CT-dataset: a CT Scan dataset about COVID-19. arXiv preprint arXiv:2003.13865 (2020)"}],"container-title":["Communications in Computer and Information Science","Recent Challenges in Intelligent Information and Database Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-42430-4_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T13:34:22Z","timestamp":1730208862000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-42430-4_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031424298","9783031424304"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-42430-4_40","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"29 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACIIDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Intelligent Information and Database Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Phuket","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aciids2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aciids.pwr.edu.pl\/2023\/","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":"224","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":"50","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":"0","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":"22% - 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":"3,87","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":"2,82","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}