Predicting the Lineage Choice of Hematopoietic Stem Cells : A Novel Approach Using Deep Neural Networks

Language: English

Published by Springer Fachmedien Wiesbaden, Springer Fachmedien Wiesbaden, 2016

365812878X / 9783658128784

Series: Book 30 of 91 - BestMasters

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - Manuel Kroiss examines the differentiation of hematopoietic stem cells using machine learning methods. This work is based on experiments focusing on the lineage choice of CMPs, the progenitors of HSCs, which either become MEP or GMP cells. The author presents a novel approach to distinguish MEP from GMP cells using machine learning on morphology features extracted from bright field images. He tests the performance of different models and focuses on Recurrent Neural Networks with the latest advances from the field of deep learning. Two different improvements to recurrent networks were tested: Long Short Term Memory (LSTM) cells that are able to remember information over long periods of time, and dropout regularization to prevent overfitting. With his method, Manuel Kroiss considerably outperforms standard machine learning methods without time information like Random Forests and Support Vector Machines.

Seller Inventory # 9783658128784

Title
Predicting the Lineage Choice of Hematopoietic Stem Cells : A Novel Approach Using Deep Neural Networks
Author
Manuel Kroiss
Publisher
Springer Fachmedien Wiesbaden, Springer Fachmedien Wiesbaden
Publication year
2016
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
365812878X
ISBN 13
9783658128784
Item weight
122 grams
Dimensions
210x148x6 mm
Series
Book 30 of 91: BestMasters

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item30 to 40 business days7 to 14 business days
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