{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T03:58:28Z","timestamp":1649131108709},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,1,14]],"date-time":"2022-01-14T00:00:00Z","timestamp":1642118400000},"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":[[2022,1,14]]},"abstract":"<jats:p>The possibility of postoperative speech dysfunction prediction in neurosurgery based on intraoperative cortico-cortical evoked potentials (CCEP) might provide a new basis to refine the criteria for the extent of intracerebral tumor resection and preserve patients\u2019 quality of life. In this study, we aimed to test the quality of predicting postoperative speech dysfunction with machine learning based on the initial intraoperative CCEP before tumor removal. CCEP data were reported for 26 patients. We used several machine learning models to predict speech deterioration following neurosurgery: a random forest of decision trees, logistic regression, support vector machine with different types of the kernel (linear, radial, and polynomial). The best result with F1-score = 0.638 was obtained by a support vector machine with a polynomial kernel. Most models showed low specificity and high sensitivity (reached 0.993 for the best model). Our pilot study demonstrated the insufficient quality of speech dysfunction prediction by solely intraoperative CCEP recorded before glial tumor resection, grounding our further research of CCEP postresectional dynamics.<\/jats:p>","DOI":"10.3233\/shti210852","type":"book-chapter","created":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T15:46:56Z","timestamp":1642434416000},"source":"Crossref","is-referenced-by-count":0,"title":["Prediction of Postoperative Speech Dysfunction Based on Cortico-Cortical Evoked Potentials and Machine Learning"],"prefix":"10.3233","author":[{"given":"Timur","family":"Ishankulov","sequence":"first","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gleb","family":"Danilov","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Pitskhelauri","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oleg","family":"Titov","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna","family":"Ogurtsova","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Svetlana","family":"Buklina","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evgeniy","family":"Gulaev","sequence":"additional","affiliation":[{"name":"National Medical Research Center of Traumatology and Orthopedics named after N.N. Priorov, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tatyana","family":"Konakova","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrey","family":"Bykanov","sequence":"additional","affiliation":[{"name":"Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Informatics and Technology in Clinical Care and Public Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI210852","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T15:46:57Z","timestamp":1642434417000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI210852"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,14]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti210852","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,14]]}}}