{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T22:36:54Z","timestamp":1779403014562,"version":"3.53.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686615","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,21]]},"abstract":"<jats:p>Algorithms for object detection, particularly those based on YOLO, have demonstrated impressive effectiveness in achieving a balance between accuracy and speed. Their use in medical imaging has shown promise, but remains underexplored. In this study, a YOLO-like model is proposed that focuses on detecting lung pathologies in X-ray images, is based on YOLOv5, and uses Squeeze-and-Excite and Residual Blocks. It outperforms most YOLO and YOLO-like architectures in terms of accuracy, and compared to YOLOv5, experiments showed an increase in recall and mAP@50 of 3.3% and 1.5%, respectively. The suggested architecture yields encouraging results, establishing itself as a cutting-edge solution for accurate and efficient detection of pathologies in chest X-rays. The code implementation of this project is publicly available at: https:\/\/github.com\/GKatsagannis\/YOLO-LXR<\/jats:p>","DOI":"10.3233\/shti260099","type":"book-chapter","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T21:55:16Z","timestamp":1779400516000},"source":"Crossref","is-referenced-by-count":0,"title":["YOLO-LXR: An Enhanced Model for Pathology Detection in Chest X-Rays"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5672-5616","authenticated-orcid":false,"given":"Gerasimos","family":"Katsagannis","sequence":"first","affiliation":[{"name":"Bioengineering Research Group, Cardiff Metropolitan University, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4360-5902","authenticated-orcid":false,"given":"Barry L.","family":"Bentley","sequence":"additional","affiliation":[{"name":"Bioengineering Research Group, Cardiff Metropolitan University, United Kingdom"},{"name":"Massachusetts General Hospital & Harvard Medical School, Boston, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Opening the Personal Gate between Technology and Health Care"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI260099","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T21:55:16Z","timestamp":1779400516000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI260099"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,21]]},"ISBN":["9781643686615"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti260099","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,21]]}}}