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dc.contributor.author | Vega A.V. | |
dc.contributor.author | Madrigal O.C. | |
dc.contributor.author | Kugurakova V. | |
dc.date.accessioned | 2022-02-09T20:48:25Z | |
dc.date.available | 2022-02-09T20:48:25Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 2367-3370 | |
dc.identifier.uri | https://dspace.kpfu.ru/xmlui/handle/net/170421 | |
dc.description.abstract | Virtual Reality simulators allow surgical training in a safe and controlled environment. Through simulation, procedures can be repeated until a certain level of skill is acquired. This paper presents a fuzzy logic model implemented separately from the Virtual Reality simulator so that it can be used from other simulators. Multiple linear regression is applied for training using a Python library. The model is part of a self-adaptive model for a Virtual Reality-based surgery simulator. | |
dc.relation.ispartofseries | Lecture Notes in Networks and Systems | |
dc.subject | Appendectomy | |
dc.subject | Fuzzy logic | |
dc.subject | Surgery | |
dc.subject | Virtual reality | |
dc.title | Fuzzy Control Model to Determine the Score in Virtual Reality-Based Appendectomy Practices | |
dc.type | Conference Proceeding | |
dc.relation.ispartofseries-volume | 232 LNNS | |
dc.collection | Публикации сотрудников КФУ | |
dc.relation.startpage | 899 | |
dc.source.id | SCOPUS23673370-2021-232-SID85120581541 |