{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T01:47:15Z","timestamp":1789609635372,"version":"build-2803163510"},"reference-count":42,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,1,22]],"date-time":"2025-01-22T00:00:00Z","timestamp":1737504000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100014809","name":"Technology Agency of the Czech Republic","doi-asserted-by":"publisher","award":["TL05000177"],"award-info":[{"award-number":["TL05000177"]}],"id":[{"id":"10.13039\/100014809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Dyslexia"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>Current diagnostic methods for dyslexia primarily rely on traditional paper\u2010and\u2010pencil tasks. Advanced technological approaches, including eye\u2010tracking and artificial intelligence (AI), offer enhanced diagnostic capabilities. In this paper, we bridge the gap between scientific and diagnostic concepts by proposing a novel dyslexia detection method, called INSIGHT, which combines a visualisation phase and a neural network\u2010based classification phase. The first phase involves transforming eye\u2010tracking fixation data into 2D visualisations called Fix\u2010images, which clearly depict reading difficulties. The second phase utilises the ResNet18 convolutional neural network for classifying these images. The INSIGHT method was tested on 35 child participants (13 dyslexic and 22 control readers) using three text\u2010reading tasks, achieving a highest accuracy of 86.65%. Additionally, we cross\u2010tested the method on an independent dataset of Danish readers, confirming the robustness and generalizability of our approach with a notable accuracy of 86.11%. This innovative approach not only provides detailed insight into eye movement patterns when reading but also offers a robust framework for the early and accurate diagnosis of dyslexia, supporting the potential for more personalised and effective interventions.<\/jats:p>","DOI":"10.1002\/dys.1801","type":"journal-article","created":{"date-parts":[[2025,1,23]],"date-time":"2025-01-23T03:40:40Z","timestamp":1737603640000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["<scp>INSIGHT<\/scp>: Combining Fixation Visualisations and Residual Neural Networks for Dyslexia Classification From Eye\u2010Tracking Data"],"prefix":"10.1002","volume":"31","author":[{"given":"Roman","family":"Svaricek","sequence":"first","affiliation":[{"name":"Department of Educational Sciences, Faculty of Arts Masaryk University  Brno Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3472-1514","authenticated-orcid":false,"given":"Nicol","family":"Dostalova","sequence":"additional","affiliation":[{"name":"Department of Educational Sciences, Faculty of Arts Masaryk University  Brno Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7668-8521","authenticated-orcid":false,"given":"Jan","family":"Sedmidubsky","sequence":"additional","affiliation":[{"name":"Department of Machine Learning and Data Processing, Faculty of Informatics Masaryk University  Brno Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrej","family":"Cernek","sequence":"additional","affiliation":[{"name":"Department of Machine Learning and Data Processing, Faculty of Informatics Masaryk University  Brno Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,1,22]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/BIBE.2019.00145"},{"key":"e_1_2_11_3_1","unstructured":"Bedn\u00e1\u0159ov\u00e1 J.2015.\u201cDiagnostika schopnost\u00ed a dovednost\u00ed v oblasti \u010dten\u00ed a psan\u00ed. Varianta pro pedagogy \u0161kol a \u0161koln\u00ed poradensk\u00e1 pracovi\u0161t\u011b 3.\u20144.ro\u010dn\u00edk. 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