{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,15]],"date-time":"2024-09-15T19:05:10Z","timestamp":1726427110466},"reference-count":50,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2020,11,11]],"date-time":"2020-11-11T00:00:00Z","timestamp":1605052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Fundaci\u00f3n Canaria de Investigaci\u00f3n Sanitaria","award":["PIFUN23\/18"],"award-info":[{"award-number":["PIFUN23\/18"]}]},{"name":"Spanish Ministry of Education, Culture and Sport","award":["FPU15\/0334"],"award-info":[{"award-number":["FPU15\/0334"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Closed-loop administration of propofol for the control of hypnosis in anesthesia has evidenced an outperformance when comparing it with manual administration in terms of drug consumption and post-operative recovery of patients. Unlike other systems, the success of this strategy lies on the availability of a feedback variable capable of quantifying the current hypnotic state of the patient. However, the appearance of anomalies during the anesthetic process may result in inaccurate actions of the automatic controller. These anomalies may come from the monitors, the syringe pumps, the actions of the surgeon or even from alterations in patients. This could produce adverse side effects that can affect the patient postoperative and reduce the safety of the patient in the operating room. Then, the use of anomaly detection techniques plays a significant role to avoid this undesirable situations. This work assesses different one-class intelligent techniques to detect anomalies in patients undergoing general anesthesia. Due to the difficulty of obtaining real data from anomaly situations, artificial outliers are generated to check the performance of each classifier. The final model presents successful performance.<\/jats:p>","DOI":"10.1093\/jigpal\/jzaa065","type":"journal-article","created":{"date-parts":[[2020,9,29]],"date-time":"2020-09-29T11:33:53Z","timestamp":1601379233000},"page":"326-341","source":"Crossref","is-referenced-by-count":9,"title":["One-Class-Based Intelligent Classifier for Detecting Anomalous Situations During the Anesthetic Process"],"prefix":"10.1093","volume":"30","author":[{"given":"Alberto","family":"Leira","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, University of A Coru\u00f1a (UDC), CTC, CITIC, Avda. 19 de febrero s\/n, 15405, Ferrol, A Coru\u00f1a, Spain"}]},{"given":"Esteban","family":"Jove","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of A Coru\u00f1a (UDC), CTC, CITIC, Avda. 19 de febrero s\/n, 15405, Ferrol, A Coru\u00f1a, Spain"}]},{"given":"Jose M","family":"Gonzalez-Cava","sequence":"additional","affiliation":[{"name":"Department of Computer Science and System Engineering, University of La Laguna (ULL), Avda. 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Francisco S\u00e1nchez s\/n, 38200, S\/C de Tenerife, Spain"}]},{"given":"Jos\u00e9-Luis","family":"Casteleiro-Roca","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of A Coru\u00f1a (UDC), CTC, CITIC, Avda. 19 de febrero s\/n, 15405, Ferrol, A Coru\u00f1a, Spain"}]},{"given":"H\u00e9ctor","family":"Quinti\u00e1n","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of A Coru\u00f1a (UDC), CTC, CITIC, Avda. 19 de febrero s\/n, 15405, Ferrol, A Coru\u00f1a, Spain"}]},{"given":"Francisco","family":"Zayas-Gato","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of A Coru\u00f1a (UDC), CTC, CITIC, Avda. 19 de febrero s\/n, 15405, Ferrol, A Coru\u00f1a, Spain"}]},{"given":"Santiago Torres","family":"\u00c1lvarez","sequence":"additional","affiliation":[{"name":"Department of Computer Science and System Engineering, University of La Laguna (ULL), Avda. Astrof. Francisco S\u00e1nchez s\/n, 38200, S\/C de Tenerife, Spain"}]},{"given":"Svetlana","family":"Simi\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia"}]},{"given":"Juan-Albino","family":"M\u00e9ndez-P\u00e9rez","sequence":"additional","affiliation":[{"name":"Department of Computer Science and System Engineering, University of La Laguna (ULL), Avda. Astrof. Francisco S\u00e1nchez s\/n, 38200, S\/C de Tenerife, Spain"}]},{"given":"Jos\u00e9","family":"Luis Calvo-Rolle","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of A Coru\u00f1a (UDC), CTC, CITIC, Avda. 19 de febrero s\/n, 15405, Ferrol, A Coru\u00f1a, Spain"}]}],"member":"286","published-online":{"date-parts":[[2020,11,11]]},"reference":[{"key":"2022032112132686900_ref1","doi-asserted-by":"crossref","first-page":"2740","DOI":"10.3390\/s19122740","article-title":"A fault detection system for a geothermal heat exchanger sensor based on intelligent techniques","author":"Al\u00e1iz-Moret\u00f3n","year":"2019","journal-title":"Sensors"},{"key":"2022032112132686900_ref2","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.energy.2018.12.207","article-title":"Geothermal heat exchanger energy prediction based on time series and monitoring sensors 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