A machine learning model for predicting the lymph node metastasis of early gastric cancer not meeting the endoscopic curability criteria.
Minoru KatoYoshito HayashiRyotaro UemaTakashi KanesakaShinjiro YamaguchiAkira MaekawaTakuya YamadaMasashi YamamotoShinji KitamuraTakuya InoueShunsuke YamamotoTakashi KizuRisato TakedaHideharu OgiyamaKatsumi YamamotoKenji AoiKoji NagaikeYasutaka SasaiSatoshi EgawaHaruki AkamatsuHiroyuki OgawaMasato KomoriNishihara AkihiroTakeo YoshiharaYoshiki TsujiiTetsuo TakeharaPublished in: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association (2024)
Our ML model performed better than the eCura system for predicting LNM risk in patients with EGC who did not meet the existing Japanese endoscopic curability criteria. We developed a neural network-based machine learning model that predicts the risk of lymph node metastasis in patients with early gastric cancer who did not meet the endoscopic curability criteria.