The aim of this study is to establish a deep learning (DL) model to predict the pathological type of gastric adenocarcinoma cancer based on whole-slide images(WSIs). We downloaded 356 histopathological images of gastric adenocarcinoma (STAD) patients...
Cancer imaging : the official publication of the International Cancer Imaging Society
Jul 30, 2024
BACKGROUND: Survival prognosis of patients with gastric cancer (GC) often influences physicians' choice of their follow-up treatment. This study aimed to develop a positron emission tomography (PET)-based radiomics model combined with clinical tumor-...
Gastric cancer remains a significant global health concern, with a notably high incidence in East Asia. This paper explores the potential of explainable machine learning models in enhancing the early diagnosis of gastric cancer. Through comprehensive...
BACKGROUND: Artificial intelligence (AI) using deep learning systems has recently been utilized in various medical fields. In the field of gastroenterology, AI is primarily implemented in image recognition and utilized in the realm of gastrointestina...
The study aims to investigate the predictive capability of machine learning algorithms for omental metastasis in locally advanced gastric cancer (LAGC) and to compare the performance metrics of various machine learning predictive models. A retrospect...
PURPOSE: Laparoscopic distal gastrectomy (LDG) is a difficult procedure for early career surgeons. Artificial intelligence (AI)-based surgical step recognition is crucial for establishing context-aware computer-aided surgery systems. In this study, w...
PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fusion (MMF) model using F-fluorodeoxyglucose (FDG) PET/CT radiomics and kernelled support tensor machine (KSTM), integrated with clinical factors and nu...
Postoperative venous thromboembolic events (VTEs), such as lower extremity deep vein thrombosis (DVT), are major risk factors for gastric cancer (GC) patients following radical gastrectomy. Accurately predicting and managing these risks is crucial fo...
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Jul 2, 2024
BACKGROUND: Accurate prediction of pathologic results for early gastric cancer (EGC) based on endoscopic findings is essential in deciding between endoscopic and surgical resection. This study aimed to develop an artificial intelligence (AI) model to...
PURPOSE: To evaluate the image quality of ultra-high-resolution CT (U-HRCT) images reconstructed using an improved deep-learning-reconstruction (DLR) method. Additionally, we assessed the utility of U-HRCT in visualizing gastric wall structure, detec...
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