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Two versions of the model were created using either chest X-rays (Model A) or natural images (Model B) as pre-training data. We retrospectively collected 600 CTPAs to use in training and validation and 200 CTPAs to use in testing. CTPAs were annotated only with binary labels on both stack- and slice-based levels. Performance of the models was evaluated with ROC and precision\u2013recall curves, specificity, sensitivity, accuracy, as well as positive and negative predictive values.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Both models performed well on both stack- and slice-based levels. On the stack-based level, Model A reached specificity and sensitivity of 93.5% and 86.6%, respectively, outperforming Model B slightly (specificity 90.7% and sensitivity 83.5%). However, the difference between their ROC AUC scores was not statistically significant (0.94 vs 0.91,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.07).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We show that a deep learning model trained with a relatively small, weakly annotated dataset can achieve excellent performance results in detecting PE from CTPAs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12880-022-00763-z","type":"journal-article","created":{"date-parts":[[2022,3,13]],"date-time":"2022-03-13T23:02:53Z","timestamp":1647212573000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["Automated detection of pulmonary embolism from CT-angiograms using deep learning"],"prefix":"10.1186","volume":"22","author":[{"given":"Heidi","family":"Huhtanen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mikko","family":"Nyman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tarek","family":"Mohsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arho","family":"Virkki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antti","family":"Karlsson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jussi","family":"Hirvonen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,3,14]]},"reference":[{"issue":"6","key":"763_CR1","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1001\/archinte.158.6.585","volume":"158","author":"MD Silverstein","year":"1998","unstructured":"Silverstein MD, Heit JA, Mohr DN, Petterson TM, O\u2019Fallon WM, Melton LJ. 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The study was conducted in accordance with the Declaration of Helsinki. Waiver for written patient consent was not sought from the institutional review board (IRB, called the Ethics Committee of The Hospital District of Southwest Finland), because it is not required by the national legislature for retrospective studies of existing data (e.g. registry data). Institutional review board review (approval or waiver) was not sought, because it is not required by the national legislature for retrospective studies of existing data. Registry studies in Finland are exempted from ethical approval by law, and are only subject to hospital district permission. This is based on the following legislature: Law on the secondary use of social and health data (552\/2019), Data protection act (1050\/2018), Act on the publicity of the activities of authorities (621\/1999), and the EU GDPR (2016\/679). Legislature is publicly available at\n                      \n                      (most laws and decrees are only available in Finnish and Swedish). For any additional inquiries, please contact Turku Research Services at\n                      \n                      .","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors have read the journal\u2019s policy and have the following potentially competing interests: T.M. was an employee of Reaktor Innovations Oy at the time of the study. The other authors have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"43"}}