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Stomach Neoplasms

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A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cancer has become a complex health problem due to its high mortality. Over the past few decades, with the rapid development of the high-throughput sequencing technology and the application of various machine learning methods...

Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Clinical cancer research : an official journal of the American Association for Cancer Research
Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We constructed a classifier to predict prognosis and identify a subset of patients who can benefit from...

Weakly Supervised Biomedical Image Segmentation by Reiterative Learning.

IEEE journal of biomedical and health informatics
Recent advances in deep learning have produced encouraging results for biomedical image segmentation; however, outcomes rely heavily on comprehensive annotation. In this paper, we propose a neural network architecture and a new algorithm, known as ov...

Gastric Pathology Image Classification Using Stepwise Fine-Tuning for Deep Neural Networks.

Journal of healthcare engineering
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...

Prediction of Overall Survival and Novel Classification of Patients with Gastric Cancer Using the Survival Recurrent Network.

Annals of surgical oncology
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.

Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
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 ...

Serum microRNA panel excavated by machine learning as a potential biomarker for the detection of gastric cancer.

Oncology reports
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...

5-fluorouracil combined with cisplatin and mitomycin C as an optimized regimen for hyperthermic intraperitoneal chemotherapy in gastric cancer.

Journal of surgical oncology
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...

Enhanced antitumor efficacy of doxorubicin-encapsulated halloysite nanotubes.

International journal of nanomedicine
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 ...