Computational Analysis and Classification of Hernia Repairs
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064190%3A_____%2F24%3A10001237" target="_blank" >RIV/00064190:_____/24:10001237 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/24:00380699 RIV/00216208:11110/24:10479949 RIV/70883521:28140/24:63584698 RIV/60461373:22340/24:43930501 RIV/00064203:_____/24:10479949
Result on the web
<a href="https://doi.org/10.3390/app14083236" target="_blank" >https://doi.org/10.3390/app14083236</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/app14083236" target="_blank" >10.3390/app14083236</a>
Alternative languages
Result language
angličtina
Original language name
Computational Analysis and Classification of Hernia Repairs
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30230 - Other clinical medicine subjects
Result continuities
Project
<a href="/en/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotics and advanced industrial production</a><br>
Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
APPLIED SCIENCES-BASEL
ISSN
2076-3417
e-ISSN
2076-3417
Volume of the periodical
14
Issue of the periodical within the volume
8
Country of publishing house
CH - SWITZERLAND
Number of pages
14
Pages from-to
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UT code for WoS article
001210081400001
EID of the result in the Scopus database
2-s2.0-85192575393