{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T08:40:45Z","timestamp":1791362445290,"version":"4.3.1"},"reference-count":28,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T00:00:00Z","timestamp":1667174400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2019YFC0118805"],"award-info":[{"award-number":["2019YFC0118805"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Mycoses"],"published-print":{"date-parts":[[2023,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Currently, the diagnosis of invasive pulmonary aspergillosis (IPA) mainly depends on the integration of clinical, radiological and microbiological data. Artificial intelligence (AI) has shown great advantages in dealing with data\u2010rich biological and medical challenges, but the literature on IPA diagnosis is rare.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to provide a non\u2010invasive, objective and easy\u2010to\u2010use AI approach for the early diagnosis of IPA.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We generated a prototype diagnostic deep learning model (IPA\u2010NET) comprising three interrelated computation modules for the automatic diagnosis of IPA. First, IPA\u2010NET was subjected to transfer learning using 300,000 CT images of non\u2010fungal pneumonia from an online database. Second, training and internal test sets, including clinical features and chest CT images of patients with IPA and non\u2010fungal pneumonia in the early stage of the disease, were independently constructed for model training and internal verification. Third, the model was further validated using an external test set.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>IPA\u2010NET showed a marked diagnostic performance for IPA as verified by the internal test set, with an accuracy of 96.8%, a sensitivity of 0.98, a specificity of 0.96 and an area under the curve (AUC) of 0.99. When further validated using the external test set, IPA\u2010NET showed an accuracy of 89.7%, a sensitivity of 0.88, a specificity of 0.91 and an AUC of 0.95.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This novel deep learning model provides a non\u2010invasive, objective and reliable method for the early diagnosis of IPA.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/myc.13540","type":"journal-article","created":{"date-parts":[[2022,10,22]],"date-time":"2022-10-22T03:13:16Z","timestamp":1666408396000},"page":"118-127","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Prototype early diagnostic model for invasive pulmonary aspergillosis based on deep learning and big data training"],"prefix":"10.1111","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8984-6795","authenticated-orcid":false,"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"School of Biomedical Engineering Southern Medical University  Guangzhou China"},{"name":"Department of Information, Zhujiang Hospital Southern Medical University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mujiao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering Southern Medical University  Guangzhou China"},{"name":"Department of Information Guangzhou First People's Hospital  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peimin","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Information Center Guangzhou Chest Hospital  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2869-9488","authenticated-orcid":false,"given":"Hua","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine Zhujiang Hospital, Southern Medical University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7699-3446","authenticated-orcid":false,"given":"Jing","family":"Cai","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine Zhujiang Hospital, Southern Medical University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine Zhujiang Hospital, Southern Medical University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Information, Nanfang Hospital Southern Medical University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zelin","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Surgery Guangzhou Chest Hospital  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingdong","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of Information, Nanfang Hospital Southern Medical University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaomin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering Southern Medical University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingwen","family":"Lv","sequence":"additional","affiliation":[{"name":"Department of Information, Zhujiang Hospital Southern Medical University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,10,31]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra2027424"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.12703\/P6-81"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmi.2018.01.002"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/cid\/ciw444"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1111\/myc.12881"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1159\/000196477"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature21056"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.11.005"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.104003"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2016.10.007"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/BMEiCON.2018.8609997"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics10090649"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-021-07715-1"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104348"},{"key":"e_1_2_10_16_1","first-page":"TE01","article-title":"Pulmonary aspergillosis: what CT can offer before it is too late!","volume":"10","author":"Prasad A","year":"2016","journal-title":"J Clin Diagn Res"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2020.08.029"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01228-7"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_2_10_23_1","first-page":"1409.1556","volume-title":"Very deep convolutional networks for large\u2010scale image recognition","author":"Simonyan K","year":"2014"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"e_1_2_10_25_1","first-page":"1097","volume-title":"Proceedings of 26th Annual Conference on Neural Information Processing Systems (NIPS'12)","author":"Krizhevsky A","year":"2013"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btr597"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-011-0012-5"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.15537\/smj.2019.2.22940"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201111-1978OC"}],"container-title":["Mycoses"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/myc.13540","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/myc.13540","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/myc.13540","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,20]],"date-time":"2023-08-20T07:38:39Z","timestamp":1692517119000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/myc.13540"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,31]]},"references-count":28,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["10.1111\/myc.13540"],"URL":"https:\/\/doi.org\/10.1111\/myc.13540","archive":["Portico"],"relation":{},"ISSN":["0933-7407","1439-0507"],"issn-type":[{"value":"0933-7407","type":"print"},{"value":"1439-0507","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,31]]},"assertion":[{"value":"2022-06-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-10-19","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-10-31","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}