{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T12:01:45Z","timestamp":1791892905893,"version":"4.3.4"},"reference-count":47,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T00:00:00Z","timestamp":1791590400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Technology and Health Care"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Fibromyalgia is a chronic pain disorder associated with sleep disturbance and substantial functional burden.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study evaluated a self-organized explainable feature engineering (SOXFE) model for EEG-based fibromyalgia classification.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A previously reported sleep EEG dataset from a 32-participant source cohort was analyzed separately for NREM Stage 2 and Stage 3. The analysis-ready version contained 136 labeled stage-record files: 74 for Stage 2 and 62 for Stage 3. The SOXFE model comprised LTPat feature extraction, training-only CWNCA feature selection, tkNN classification, IMV information fusion, and DLob-based explanation. Record-wise LORO was primary; segment-level 10-fold cross-validation was complementary.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Record-wise LORO used 74 outer folds for Stage 2 and 62 for Stage 3. Descriptive pooled held-out-epoch accuracy was 92.77% (95% CI: 91.76\u201393.67) for Stage 2 and 97.00% (95% CI: 96.22\u201397.63) for Stage 3. Every epoch from the held-out recording was excluded from training and selection. Complementary segment-level 10-fold cross-validation yielded 100.00% accuracy for both stages but was not used as evidence of record-wise generalization.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The model provided record-disjoint classification and traceable model-derived explanations in this single-source dataset. LORO prevented within-record epoch leakage. However, participant linkage was unavailable, so records from the same person may have occurred across outer partitions and the reported values may overestimate person-independent performance. Verified subject-wise validation is required before clinical use.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/09287329261495183","type":"journal-article","created":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T07:32:08Z","timestamp":1791617528000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["LTPat-based SOXFE: A self-organized explainable feature engineering model for automated fibromyalgia detection"],"prefix":"10.1177","author":[{"given":"Yasemin","family":"Kirik","sequence":"first","affiliation":[{"name":"Department of Clinical Microbiology and Infectious Diseases, Fethi Sekin City Hospital, Elazig, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Serkan","family":"Kirik","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Division of Pediatric Neurology, Fethi Sekin City Hospital, Elazig, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Omer Faruk","family":"Goktas","sequence":"additional","affiliation":[{"name":"Department of Electronics and Automation, Technical Sciences Vocational School, Ankara Yildirim Beyazit University, Ankara, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Burak","family":"Tasci","sequence":"additional","affiliation":[{"name":"Vocational School of Technical Sciences, Firat University, Elazig, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sengul","family":"Dogan","sequence":"additional","affiliation":[{"name":"Department of Digital Forensics Engineering, Technology Faculty, Firat University, Elazig, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Turker","family":"Tuncer","sequence":"additional","affiliation":[{"name":"Department of Digital Forensics Engineering, Technology Faculty, Firat University, Elazig, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,10,10]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/medicina60020272"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics14161758"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41584-022-00873-6"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2021.673962"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2021.10.021"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2024.1394865"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.3390\/biomedicines12081744"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1113\/JP286639"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2023.108758"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2024.120634"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.4324\/9781003526438-17"},{"key":"e_1_3_2_13_2","first-page":"1","article-title":"Deciphering the role of sleep in fibromyalgia syndrome","volume":"3","author":"Fatima G","year":"2016","unstructured":"Fatima G, Kumar Das S. 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