Deep learning using convolutional neural networks (CNNs) is a distinguished tool for many image classification tasks. Due to its outstanding robustness and generalization, it is also expected to play a key role to facilitate advanced computer-aided d...
BACKGROUND: Artificial neural networks (ANNs) have been applied to many prediction and classification problems, and could also be used to develop a prediction model of survival outcomes for cancer patients.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Jan 15, 2018
BACKGROUND: Image recognition using artificial intelligence with deep learning through convolutional neural networks (CNNs) has dramatically improved and been increasingly applied to medical fields for diagnostic imaging. We developed a CNN that can ...
Early detection of gastric cancer (GC) is crucial to improve the therapeutic effect and prolong the survival of patients. MicroRNAs (miRNAs) are a group of small non-protein-coding RNAs that function as repressors of diverse genes. We aimed to identi...
BACKGROUND AND OBJECTIVES: Optimized drug regimens for hyperthermic intraperitoneal chemotherapy (HIPEC) have not been standardized completely in patients with advanced gastric cancer (GC). We evaluated an optimized anti-tumor protocol comprising 5-f...
International journal of nanomedicine
Dec 19, 2017
To improve the antitumor efficacy of doxorubicin (DOX) and provide novel clinical treatment of gastric cancer, halloysite nanotubes (HNTs) loaded with DOX were encapsulated by soybean phospholipid (LIP) and the formed HNTs/DOX/LIP was systematically ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 16, 2017
Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric...
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Jun 2, 2017
BACKGROUND: Automated image analysis has been developed currently in the field of surgical pathology. The aim of the present study was to evaluate the classification accuracy of the e-Pathologist image analysis software.
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