Academic Journal
Explainable artificial intelligence prediction-based model in laparoscopic liver surgery for segments 7 and 8: an international multicenter study
| العنوان: | Explainable artificial intelligence prediction-based model in laparoscopic liver surgery for segments 7 and 8: an international multicenter study |
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| المؤلفون: | Lopez-Lopez, Victor, Morise, Zenichi, Albaladejo-González, Mariano, Gómez Gavara, Concepción, Goh, Brian, Koh, Ye Xin, Dalmau, Mar |
| المساهمون: | Institut Català de la Salut, Lopez Lopez V Department of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de La Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain. Morise Z Department of Surgery, Fujita Health University School of Medicine Okazaki Medical Center, Okazaki, Aichi, Japan. Albaladejo González M Department of Information and Communication Engineering, Murcia University, Murcia, Spain. Gomez Gavara C, Dalmau M Servei de Cirurgia Hepatobiliopancreàtica i Trasplantaments, Vall d’Hebron Hospital Universitari, Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra, Spain. Goh BKP, Koh YX Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital and National Cancer Centre Singapore, Singapore, Singapore. Surgery Academic Clinical Programme, Duke-National University of Singapore Medical School, Singapore, Singapore, Vall d'Hebron Barcelona Hospital Campus |
| المصدر: | Scientia |
| بيانات النشر: | Springer |
| سنة النشر: | 2024 |
| مصطلحات موضوعية: | Fetge - Càncer - Cirurgia, Intel·ligència artificial - Aplicacions a la medicina, Cirurgia laparoscòpica, DISEASES::Neoplasms::Neoplasms by Site::Digestive System Neoplasms::Liver Neoplasms, Other subheadings::Other subheadings::Other subheadings::/surgery, PHENOMENA AND PROCESSES::Mathematical Concepts::Algorithms::Artificial Intelligence, ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Surgical Procedures, Operative::Minimally Invasive Surgical Procedures::Endoscopy::Laparoscopy, ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias del sistema digestivo::neoplasias hepáticas, Otros calificadores::Otros calificadores::Otros calificadores::/cirugía, FENÓMENOS Y PROCESOS::conceptos matemáticos::algoritmos::inteligencia artificial, TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::intervenciones quirúrgicas::procedimientos quirúrgicos mínimamente invasivos::endoscopia::laparoscopia |
| الوصف: | Artificial intelligence; Liver resection; Minimally invasive surgery ; Inteligencia artificial; Resección hepática; Cirugía mínimamente invasiva ; Intel·ligència artificial; Resecció hepàtica; Cirurgia mínimament invasiva ; Background Artificial intelligence (AI) is becoming more useful as a decision-making and outcomes predictor tool. We have developed AI models to predict surgical complexity and the postoperative course in laparoscopic liver surgery for segments 7 and 8. Methods We included patients with lesions located in segments 7 and 8 operated by minimally invasive liver surgery from an international multi-institutional database. We have employed AI models to predict surgical complexity and postoperative outcomes. Furthermore, we have applied SHapley Additive exPlanations (SHAP) to make the AI models interpretable. Finally, we analyzed the surgeries not converted to open versus those converted to open. Results Overall, 585 patients and 22 variables were included. Multi-layer Perceptron (MLP) showed the highest performance for predicting surgery complexity and Random Forest (RF) for predicting postoperative outcomes. SHAP detected that MLP and RF gave the highest relevance to the variables “resection type” and “largest tumor size” for predicting surgery complexity and postoperative outcomes. In addition, we explored between surgeries converted to open and non-converted, finding statistically significant differences in the variables “tumor location,” “blood loss,” “complications,” and “operation time.” Conclusion We have observed how the application of SHAP allows us to understand the predictions of AI models in surgical complexity and the postoperative outcomes of laparoscopic liver surgery in segments 7 and 8. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 1432-2218 |
| Relation: | Surgical Endoscopy;38; https://doi.org/10.1007/s00464-024-10681-6; Lopez-Lopez V, Morise Z, Albadalejo-González M, Gomez Gavara C, Goh BKP, Koh YX, et al. Explainable artificial intelligence prediction-based model in laparoscopic liver surgery for segments 7 and 8: an international multicenter study. Surg Endosc. 2024 May;38:2411–2422.; https://hdl.handle.net/11351/11473; 001156360600003 |
| DOI: | 10.1007/s00464-024-10681-6 |
| الاتاحة: | https://hdl.handle.net/11351/11473 https://doi.org/10.1007/s00464-024-10681-6 |
| Rights: | Attribution 4.0 International ; http://creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.E42DDF9D |
| قاعدة البيانات: | BASE |
| تدمد: | 14322218 |
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| DOI: | 10.1007/s00464-024-10681-6 |