AIMC Topic: Stomach Neoplasms
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Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk.
BMC medical genomics
Nov 20, 2018
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
Nov 16, 2018
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...
ROC Curve
Gastrectomy
Gastric Mucosa
Stomach Neoplasms
Image Processing, Computer-Assisted
Endoscopic Mucosal Resection
Gastroscopy
Neoplasm Invasiveness
Sensitivity and Specificity
Serous Membrane
Humans
Male
Carcinoma
Diagnosis, Computer-Assisted
Neural Networks, Computer
Artificial Intelligence
Female
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
Oct 5, 2018
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...
Humans
Software
Breast Neoplasms
Male
Diagnosis, Computer-Assisted
Deep Learning
Lung Neoplasms
Algorithms
Female
Reproducibility of Results
Stomach Neoplasms
Pattern Recognition, Automated
Sequence Analysis, RNA
False Positive Reactions
Gene Expression Regulation, Neoplastic
Supervised Machine Learning
RNA
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
Jul 24, 2018
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
Jun 25, 2018
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
Jun 21, 2018
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
Mar 1, 2018
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.
Robot-Assisted Technique for Total Gastrectomy and D2 Lymphadenectomy with Anomalous Vasculature.
Annals of surgical oncology
Feb 12, 2018
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
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 ...
Serum microRNA panel excavated by machine learning as a potential biomarker for the detection of gastric cancer.
Oncology reports
Dec 19, 2017
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...
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