scholarly journals Machine learning based approach to pH imaging and classification of single cancer cells

2021 ◽  
Vol 5 (1) ◽  
pp. 016105
Author(s):  
Y. Belotti ◽  
D. S. Jokhun ◽  
J. S. Ponnambalam ◽  
V. L. M. Valerio ◽  
C. T. Lim
Keyword(s):  
Machine Learning ◽  
Cancer Cells ◽  
Ph Imaging ◽  
Single Cancer

Semiconductor Quantum Dots for Multicolor Fluorescence Imaging and Spectroscopy of Single Cancer Cells

2003 ◽  
Vol 773 ◽  
Author(s):  
Xiaohu Gao ◽  
Shuming Nie ◽  
Wallace H. Coulter
Keyword(s):  
Quantum Dots ◽  
Cancer Cells ◽  
Fluorescence Imaging ◽  
Organic Dyes ◽  
Fluorescent Proteins ◽  
Single Cells ◽  
Quantitative Imaging ◽  
Semiconductor Quantum Dots ◽  
Single Cancer ◽  
Imaging And Spectroscopy

AbstractLuminescent quantum dots (QDs) are emerging as a new class of biological labels with unique properties and applications that are not available from traditional organic dyes and fluorescent proteins. Here we report new developments in using semiconductor quantum dots for quantitative imaging and spectroscopy of single cancer cells. We show that both live and fixed cells can be labeled with multicolor QDs, and that single cells can be analyzed by fluorescence imaging and wavelength-resolved spectroscopy. These results raise new possibilities in cancer imaging, molecular profiling, and disease staging.

A Brief Survey on Text Classification Using Various Machine Learning Techniques

2018 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Padmavathi .S ◽  
M. Chidambaram
Keyword(s):  
Machine Learning ◽  
Text Classification ◽  
Fixed Number ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Rule Based ◽  
Learning Techniques ◽  
Machine Learning Approach ◽  
Rule Based Approach

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.

Classification of Observations through Combination of the Dimension Reduction and the Cluster Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 30
Author(s):  
Hyeuk Kim
Keyword(s):  
Machine Learning ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Unsupervised Learning ◽  
Principal Component ◽  
Component Analysis ◽  
Baseball Players ◽  
Partitioning Around Medoids ◽  
Different Characteristics

Unsupervised learning in machine learning divides data into several groups. The observations in the same group have similar characteristics and the observations in the different groups have the different characteristics. In the paper, we classify data by partitioning around medoids which have some advantages over the k-means clustering. We apply it to baseball players in Korea Baseball League. We also apply the principal component analysis to data and draw the graph using two components for axis. We interpret the meaning of the clustering graphically through the procedure. The combination of the partitioning around medoids and the principal component analysis can be used to any other data and the approach makes us to figure out the characteristics easily.

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