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dc.title | Computational analysis and classification of hernia repairs | en |
dc.contributor.author | Charvátová, Hana | |
dc.contributor.author | East, Barbora | |
dc.contributor.author | Procházka, Aleš | |
dc.contributor.author | Martynek, Daniel | |
dc.contributor.author | Gonsorčíková, Lucie | |
dc.relation.ispartof | Applied Sciences (Switzerland) | |
dc.identifier.issn | 2076-3417 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.date.issued | 2024 | |
utb.relation.volume | 14 | |
utb.relation.issue | 8 | |
dc.type | article | |
dc.language.iso | en | |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | |
dc.identifier.doi | 10.3390/app14083236 | |
dc.relation.uri | https://www.mdpi.com/2076-3417/14/8/3236 | |
dc.relation.uri | https://www.mdpi.com/2076-3417/14/8/3236/pdf?version=1712909960 | |
dc.subject | hernia surgical repair | en |
dc.subject | computational intelligence | en |
dc.subject | feature extraction | en |
dc.subject | classification | en |
dc.subject | machine learning | en |
dc.description.abstract | Problems related to ventral hernia repairs (VHR) are very common, and evaluating them using computational methods can assist in selecting the most appropriate treatment. This study is based upon data from 3339 patients from different European countries observed during the last 12 years (2012–2023), which were collected by specialists in hernia surgery. Most patients underwent standard surgical procedures, with a growing trend towards laparoscopic surgery. This paper focuses on statistically evaluating the treatment methods in relation to patient age, body mass index (BMI), and the type of repair. Appropriate mathematical methods are employed to extract and classify the selected features, with emphasis on computational and machine-learning techniques. The paper presents surgical hernia treatment statistics related to patient age, BMI, and repair methods. The main conclusions point to mean groin hernia repair (GHR) complications of 19% for patients in the database. The accuracy of separating GHR mesh surgery with and without postoperative complications reached 74.4% using a two-layer neural network classification. Robotic surgeries represent 22.9% of all the evaluated hernia repairs. The proposed methodology suggests both an interdisciplinary approach and the utilization of computational intelligence in hernia surgery, potentially applicable in a clinical setting. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1012003 | |
utb.identifier.scopus | 2-s2.0-85192575393 | |
utb.identifier.wok | 001210081400001 | |
utb.source | j-scopus | |
dc.date.accessioned | 2024-08-22T12:59:40Z | |
dc.date.available | 2024-08-22T12:59:40Z | |
dc.description.sponsorship | Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT, (SENDISO - CZ.02.01.01/00/22_008/0004596); Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT | |
dc.description.sponsorship | European Union [CZ.02.01.01/00/22_008/0004590]; Operational Programme Johannes Amos Comenius; European Structural and Investment Funds; Czech Ministry of Education, Youth and Sports [SENDISO - CZ.02.01.01/00/22_008/0004596] | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.rights.access | openAccess | |
utb.contributor.internalauthor | Charvátová, Hana | |
utb.fulltext.sponsorship | This investigation was reinforced by the European Union under the project ROBOPROX (reg. no. CZ.02.01.01/00/22_008/0004590) in the area of machine learning. The research related to data acquisition was supported by Operational Programme Johannes Amos Comenius, financed by European Structural and Investment Funds and the Czech Ministry of Education, Youth and Sports (Project No. SENDISO - CZ.02.01.01/00/22_008/0004596). All data were acquired from the EHS registry (www.ehs-hernia-registry.com, (accessed on 14 February 2024)) supervised by the second author. | |
utb.fulltext.sponsorship | This research received no external funding | |
utb.wos.affiliation | [Charvatova, Hana] Tomas Bata Univ Zlin, Fac Appl Informat, Dept Environm Engn, Zlin 76001, Czech Republic; [East, Barbora] Charles Univ Prague, Fac Med 1, Dept Surg 3, Prague 15006, Czech Republic; [East, Barbora] Charles Univ Prague, Motol Univ Hosp, Prague 15006, Czech Republic; [Prochazka, Ales; Martynek, Daniel] Univ Chem & Technol Prague, Dept Math Informat & Cybernet, Prague 16000, Czech Republic; [Prochazka, Ales] Czech Tech Univ, Czech Inst Informat Robot & Cybernet, Prague 16000, Czech Republic; [Gonsorcikova, Lucie] Charles Univ Prague, Fac Med 1, Dept Pediat, Prague 14059, Czech Republic; [Gonsorcikova, Lucie] Charles Univ Prague, Thomayer Univ Hosp, Prague 14059, Czech Republic | |
utb.scopus.affiliation | Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, 760 01, Czech Republic; Third Department of Surgery, 1st Faculty of Medicine and Motol University Hospital, Charles University in Prague, Prague, 150 06, Czech Republic; Department of Mathematics, Informatics and Cybernetics, University of Chemistry and Technology in Prague, Prague, 160 00, Czech Republic; Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, 160 00, Czech Republic; Department of Pediatrics, 1st Faculty of Medicine and Thomayer University Hospital, Charles University in Prague, Prague, 140 59, Czech Republic | |
utb.fulltext.projects | CZ.02.01.01/00/22_008/0004590 | |
utb.fulltext.projects | SENDISO-CZ.02.01.01/00/22_008/0004596 |
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