Automated Detection of Hematological Patterns Through Machine Learning: Using Feature Extraction And Artificial Neural Networks for Pattern Recognition - Softcover

Rossman, Mark

 
9783659333651: Automated Detection of Hematological Patterns Through Machine Learning: Using Feature Extraction And Artificial Neural Networks for Pattern Recognition
Softcover
ISBN 10: 3659333654 ISBN 13: 9783659333651
Verlag: LAP LAMBERT Academic Publishing, 2014

Inhaltsangabe

The use of hematological analyzers has become routine in clinical practice, but the sheer volume of data produced by these devices often makes manual inspection of all the results an unwieldy task. For this reason, automated pattern analysis through the use of machine learning has been used in these types of situations, to save time and to provide invaluable aid to medical professionals in this area of diagnostic medicine. Toward this end, Artificial Neural Networks (ANNs) are often relied upon in the field of machine learning, because of their ability to distill representative feature components from large amounts of input data. This paper details an approach in which the scatterplots of cells that were produced by a hematological device were used as inputs. The data were separated into two classes, one containing clinically Normal samples, and the second containing abnormal samples that contained Variant Lymphocytes. Statistical features were extracted from these data using Principal Component Analysis (PCA) and then a Perceptron ANN was employed to differentiate between the two classes of data. The accuracy of pattern classification using this method was then discussed.

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Über die Autorin bzw. den Autor

B.S. in Electrical Engineering, Florida International University, Miami, Florida, 1999.M.S in Computer Engineering, Florida International University, Miami, Florida, 2003.Ph.D. in Electrical Engineering, Florida International University, Miami, Florida, 2011.Senior Software Engineer, Beckman Coulter Corporation, Miami, Florida, 2004-Present.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2014
Sprache
Englisch
ISBN 10 
3659333654
ISBN 13 
9783659333651
Einband
Taschenbuch
Anzahl der Seiten
128
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
Edicoes Nosso Conhecimento
customerservice@vdm-vsg.de

SIA
Riga
1039
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