{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T08:17:15Z","timestamp":1769242635269,"version":"3.49.0"},"reference-count":0,"publisher":"Caleo","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Int Adv Otol."],"abstract":"<jats:p>OBJECTIVES: Prediction of cochlear implantation (CI) outcome is often difficult because outcomes vary among patients. Though the brain plasticity\u00a0across modalities during deafness is associated with individual CI outcomes, longitudinal observations in multiple patients are scarce.\u00a0Therefore, we sought a prediction system based on cross-modal plasticity in a longitudinal study with multiple patients.\n\nMETHODS: Classification of CI outcomes between excellent or poor was tested based on the features of brain cross-modal plasticity, measured\u00a0using event-related responses and their corresponding electromagnetic sources. A machine learning estimation model was applied to 13 datasets\u00a0from 3 patients based on linear supervised training. Classification efficiency was evaluated comparing prediction accuracy, sensitivity\/specificity,\u00a0total mis-classification cost, and training time among feature set conditions.\n\nRESULTS: Combined feature sets with the sensor and source levels dramatically improved classification accuracy between excellent and poor\u00a0outcomes. Specifically, the tactile feature set best explained CI outcome (accuracy, 98.83 \u00b1 2.57%; sensitivity, 98.00 \u00b1 0.01%; specificity, 98.15 \u00b1\u00a04.26%; total misclassification cost, 0.17 \u00b1 0.38; training time, 0.51 \u00b1 0.09 sec), followed by the visual feature (accuracy, 93.50 \u00b1 4.89%; sensitivity,\u00a089.17 \u00b1 8.16%; specificity, 98.00 \u00b1 0.01%; total misclassification cost, 0.65 \u00b1 0.49; training time, 0.38 \u00b1 0.50 sec).\n\nCONCLUSION: Individual tactile and visual processing in the brain best classified the current status when classified by combined sensor\u2013source\u00a0level features. Our results suggest that cross-modal brain plasticity due to deafness may provide a basis for classifying the status. We expect this\u00a0novel method to contribute to the evaluation and prediction of CI outcomes.\n\nCite this article as: Kyong J, Suh M, Joon Han J, et al. Cross-modal cortical activity in the brain can predict cochlear implantation outcome in\u00a0adults: A machine learning study. J Int Adv Otol. 2021; 17(5): 380-386.<\/jats:p>","DOI":"10.5152\/iao.2021.9337","type":"journal-article","created":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T02:35:34Z","timestamp":1633401334000},"page":"380-386","source":"Crossref","is-referenced-by-count":7,"title":["Cross-Modal Cortical Activity in the Brain Can Predict Cochlear Implantation Outcome in Adults: A Machine Learning Study"],"prefix":"10.65717","volume":"17","author":[{"given":"Jeong-Sug","family":"Kyong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Myung-Whan","family":"Suh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jae Joon","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Moo Kyun","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tae Soo","family":"Noh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seung Ha","family":"Oh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun Ho","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55248","published-online":{"date-parts":[[2021,9,1]]},"container-title":["The Journal of International Advanced Otology"],"original-title":[],"link":[{"URL":"https:\/\/www.advancedotology.org\/index.php\/pub\/article\/download\/1554\/1552","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.advancedotology.org\/index.php\/pub\/article\/download\/1547\/1544","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.advancedotology.org\/index.php\/pub\/article\/download\/1547\/1544","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T10:41:18Z","timestamp":1769078478000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.advancedotology.org\/index.php\/pub\/article\/view\/1547"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,1]]},"references-count":0,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,9,30]]}},"URL":"https:\/\/doi.org\/10.5152\/iao.2021.9337","relation":{},"ISSN":["2148-3817"],"issn-type":[{"value":"2148-3817","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,1]]}}}