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Explainable artificial intelligence prediction-based model in laparoscopic liver surgery for segments 7 and 8: an international multicenter study.

Víctor López-LópezZeniche MoriseMariano Albaladejo-GonzálezConcepción Gomez GavaraBrian K P GohYe Xin KohSijberden Jasper PaulMohammed Abu HilalKohei MishimaJaime Arthur Pirola KrürgerPaulo HermanAlvaro CerezuelaRoberto BrusadinTakashi KaizuJuan LujanFernando RotellarKazuteru MondenMar DalmauNaoto GotohdaMasashi KudoAkishige KanazawaYutaro KatoHiroyuki NittaSatoshi AmanoRaffaele Dalla ValleMario GiuffridaMasaki UenoYuichiro OtsukaDaisuke AsanoMinoru TanabeOsamu ItanoTakuya MinagawaDilmurodjon EshmuminovIrene HerreroPablo RamírezJosé A Ruipérez-ValienteRicardo Robles-CamposGo Wakabayashi
Published in: Surgical endoscopy (2024)
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.
Keyphrases
  • artificial intelligence
  • minimally invasive
  • robot assisted
  • coronary artery bypass
  • machine learning
  • big data
  • deep learning
  • surgical site infection
  • patients undergoing
  • percutaneous coronary intervention