AIMC Topic: Stomach Neoplasms

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Spotting malignancies from gastric endoscopic images using deep learning.

Surgical endoscopy
BACKGROUND: Gastric cancer is a common kind of malignancies, with yearly occurrences exceeding one million worldwide in 2017. Typically, ulcerous and cancerous tissues develop abnormal morphologies through courses of progression. Endoscopy is a routi...

An Intelligent Clinical Decision Support System for Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to develop and validate a computational clinical decision support system (DSS) on the basis of CT radiomics features for the prediction of lymph node (LN) metastasis in gastric cancer (GC) using machine learning-bas...

Diagnosis of early gastric cancer based on fluorescence hyperspectral imaging technology combined with partial-least-square discriminant analysis and support vector machine.

Journal of biophotonics
This study investigated the feasibility of using fluorescence hyperspectral imaging technology to diagnose of early-stage gastric cancer. Fluorescence spectral images of 76 patients who were pathologically diagnosed as non-atrophic gastritis, premali...

Application of data mining methods to improve screening for the risk of early gastric cancer.

BMC medical informatics and decision making
BACKGROUND: Although gastric cancer is a malignancy with high morbidity and mortality in China, the survival rate of patients with early gastric cancer (EGC) is high after surgical resection. To strengthen diagnosing and screening is the key to impro...

Effects of ω-3 supplementation on the nutritional status, immune, and inflammatory profiles of gastric cancer patients: A randomized controlled trial.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVE: The aim of this study was to study the effect of ω-3 supplementation on the nutritional status and the immune and inflammatory profiles of patients with gastric cancer during antineoplastic pretreatment.

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk.

BMC medical genomics
BACKGROUND: With the development of sequencing technology, more and more long non-coding RNAs (lncRNAs) have been identified. Some lncRNAs have been confirmed that they play an important role in the process of development through the dosage compensat...

Application of convolutional neural network in the diagnosis of the invasion depth of gastric cancer based on conventional endoscopy.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: According to guidelines, endoscopic resection should only be performed for patients whose early gastric cancer invasion depth is within the mucosa or submucosa of the stomach regardless of lymph node involvement. The accurate pre...

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...