Full text

Turn on search term navigation

© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

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.

Details

Title
Computational Analysis and Classification of Hernia Repairs
Author
Charvátová, Hana 1   VIAFID ORCID Logo  ; East, Barbora 2   VIAFID ORCID Logo  ; Procházka, Aleš 3   VIAFID ORCID Logo  ; Martynek, Daniel 4   VIAFID ORCID Logo  ; Gonsorčíková, Lucie 5   VIAFID ORCID Logo 

 Faculty of Applied Informatics, Tomas Bata University in Zlín, 760 01 Zlín, Czech Republic 
 Third Department of Surgery, 1st Faculty of Medicine and Motol University Hospital, Charles University in Prague, 150 06 Prague, Czech Republic; [email protected] 
 Department of Mathematics, Informatics and Cybernetics, University of Chemistry and Technology in Prague, 160 00 Prague, Czech Republic; [email protected] (A.P.); [email protected] (D.M.); Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, 160 00 Prague, Czech Republic 
 Department of Mathematics, Informatics and Cybernetics, University of Chemistry and Technology in Prague, 160 00 Prague, Czech Republic; [email protected] (A.P.); [email protected] (D.M.) 
 Department of Pediatrics, 1st Faculty of Medicine and Thomayer University Hospital, Charles University in Prague, 140 59 Prague, Czech Republic; [email protected] 
First page
3236
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
20763417
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3046771531
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.