scholarly journals Name suggestions during feature identification

2016 ◽  
Author(s):  
Jabier Martinez ◽  
Tewfik Ziadi ◽  
Tegawendé F. Bissyandé ◽  
Jacques Klein ◽  
Yves Le Traon
Keyword(s):  
Feature Identification

scholarly journals Intratumoral CXCR5+CD8+T associates with favorable clinical outcomes and immunogenic contexture in gastric cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jieti Wang ◽  
Ruochen Li ◽  
Yifan Cao ◽  
Yun Gu ◽  
Hanji Fang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
T Cells ◽  
Epstein Barr Virus ◽  
Effector Memory ◽  
Feature Identification ◽  
Barr Virus ◽  
T Cell Infiltration ◽  
Epstein Barr ◽  
Gastric Cancer Patients

AbstractStudies that examined an association between CD8+T and prognosis in gastric cancer are inconsistent, and a distinct population of CXCR5+CD8+T associated with better overall survival has been reported among various malignancies. Here, we show that the abundance of intratumoral CXCR5+CD8+T cells is associated with better overall survival in patients with gastric cancer. Patients with TNM II + III gastric cancer with higher intratumoral CXCR5+CD8+T cell infiltration are more likely to benefit from adjuvant chemotherapy. Microsatellite-unstable and Epstein–Barr virus positive tumors are enriched with CXCR5+CD8+T cells. Gastric cancer infiltrating CXCR5+CD8+T cells represent a specific subtype of stem-like CD8+T with effector memory feature. Identification of the clinical significance and phenotype of gastric cancer infiltrating CXCR5+CD8+T provides a roadmap for patient stratification and trials of targeted therapies.

Online Biological Literature MRI Image Classification Study

2013 ◽  
Vol 694-697 ◽  
pp. 2336-2340
Author(s):  
Yun Feng Yang ◽  
Feng Xian Tang
Keyword(s):  
Recognition Performance ◽  
Recognition Rate ◽  
Image Features ◽  
Feature Identification ◽  
Identification Method ◽  
Image Library ◽  
Text Information ◽  
Correct Recognition Rate ◽  
Biological Literature ◽  
Mri Image

In order to construct a certain standard structure MRI (Magnetic resonance imaging) image library by extracting and collating unstructured literature data information, an identification method of the image and text information fusion is proposed. The method makes use of PHOW (Pyramid Histogram Of Words) to represent image features, combines with the word frequency characteristics of the embedded icon note (text), and then uses posterior multiplication fusion method to complete the classification and identification of the online biological literature MRI image. The experimental results show that this method has better correct recognition rate and better recognition performance than feature identification method only based on PHOW or text. The study can offer use for reference to construct other structured professional database from online literature.

Machine Learning-based Whitefly Feature Identification and Counting

2021 ◽  
Author(s):  
Kai-Chao Yao ◽  
Shih-Feng Fu ◽  
Wei-Tzer Huang ◽  
Cheng-Chun Wu
Keyword(s):  
Machine Learning ◽  
Data Storage ◽  
Ccd Camera ◽  
Machine Learning Algorithms ◽  
Feature Identification ◽  
Matching Algorithm ◽  
Vision Development ◽  
Counting Data ◽  
Image Conversion ◽  
Pyramid Matching

This article uses LabVIEW, a software program to develop a whitefly feature identification and counting technology, and machine learning algorithms for whitefly monitoring, identification, and counting applications. In addition, a high-magnification CCD camera is used for on-demand image photography, and then the functional programs of the VI library of LabVIEW NI-DAQ and LabVIEW NI Vision Development Module are used to develop image recognition functions. The grayscale-value pyramid-matching algorithm is used for image conversion and recognition in the machine learning mode. The built graphical user interface and device hardware provide convenient and effective whitefly feature identification and sample counting. This monitoring technology exhibits features such as remote monitoring, counting, data storage, and statistical analysis.

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