Artículos relacionados a Automated Detection of Hematological Patterns Through...

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

 
9783659333651: Automated Detection of Hematological Patterns Through Machine Learning: Using Feature Extraction And Artificial Neural Networks for Pattern Recognition

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

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.

Biografía del 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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Comprar nuevo

Ver este artículo

EUR 11,00 gastos de envío desde Alemania a España

Destinos, gastos y plazos de envío

Resultados de la búsqueda para Automated Detection of Hematological Patterns Through...

Imagen del vendedor

Mark Rossman
ISBN 10: 3659333654 ISBN 13: 9783659333651
Nuevo Taschenbuch
Impresión bajo demanda

Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 128 pp. Englisch. Nº de ref. del artículo: 9783659333651

Contactar al vendedor

Comprar nuevo

EUR 39,90
Convertir moneda
Gastos de envío: EUR 11,00
De Alemania a España
Destinos, gastos y plazos de envío

Cantidad disponible: 2 disponibles

Añadir al carrito

Imagen del vendedor

Mark Rossman
Publicado por LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659333654 ISBN 13: 9783659333651
Nuevo Taschenbuch
Impresión bajo demanda

Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783659333651

Contactar al vendedor

Comprar nuevo

EUR 39,90
Convertir moneda
Gastos de envío: EUR 11,99
De Alemania a España
Destinos, gastos y plazos de envío

Cantidad disponible: 1 disponibles

Añadir al carrito

Imagen del vendedor

Mark Rossman
Publicado por LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659333654 ISBN 13: 9783659333651
Nuevo Tapa blanda
Impresión bajo demanda

Librería: moluna, Greven, Alemania

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rossman MarkB.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 Internati. Nº de ref. del artículo: 5149234

Contactar al vendedor

Comprar nuevo

EUR 34,25
Convertir moneda
Gastos de envío: EUR 19,49
De Alemania a España
Destinos, gastos y plazos de envío

Cantidad disponible: Más de 20 disponibles

Añadir al carrito

Imagen de archivo

Rossman, Mark
ISBN 10: 3659333654 ISBN 13: 9783659333651
Nuevo Tapa blanda

Librería: Books Puddle, New York, NY, Estados Unidos de America

Calificación del vendedor: 4 de 5 estrellas Valoración 4 estrellas, Más información sobre las valoraciones de los vendedores

Condición: New. pp. 128. Nº de ref. del artículo: 26128412829

Contactar al vendedor

Comprar nuevo

EUR 56,12
Convertir moneda
Gastos de envío: EUR 9,89
De Estados Unidos de America a España
Destinos, gastos y plazos de envío

Cantidad disponible: 4 disponibles

Añadir al carrito

Imagen de archivo

Rossman, Mark
ISBN 10: 3659333654 ISBN 13: 9783659333651
Nuevo Tapa blanda
Impresión bajo demanda

Librería: Majestic Books, Hounslow, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: New. Print on Demand pp. 128 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Nº de ref. del artículo: 131126082

Contactar al vendedor

Comprar nuevo

EUR 57,56
Convertir moneda
Gastos de envío: EUR 10,21
De Reino Unido a España
Destinos, gastos y plazos de envío

Cantidad disponible: 4 disponibles

Añadir al carrito

Imagen de archivo

Rossman, Mark
ISBN 10: 3659333654 ISBN 13: 9783659333651
Nuevo Tapa blanda
Impresión bajo demanda

Librería: Biblios, Frankfurt am main, HESSE, Alemania

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: New. PRINT ON DEMAND pp. 128. Nº de ref. del artículo: 18128412823

Contactar al vendedor

Comprar nuevo

EUR 59,64
Convertir moneda
Gastos de envío: EUR 14,50
De Alemania a España
Destinos, gastos y plazos de envío

Cantidad disponible: 4 disponibles

Añadir al carrito

Imagen del vendedor

Mark Rossman
ISBN 10: 3659333654 ISBN 13: 9783659333651
Nuevo Taschenbuch

Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Taschenbuch. Condición: Neu. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 128 pp. Englisch. Nº de ref. del artículo: 9783659333651

Contactar al vendedor

Comprar nuevo

EUR 39,90
Convertir moneda
Gastos de envío: EUR 35,00
De Alemania a España
Destinos, gastos y plazos de envío

Cantidad disponible: 2 disponibles

Añadir al carrito