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Predicting the lineage choice of hematopoietic stem cells : a novel approach using deep neural networks

Author: Manuel Kroiss
Publisher: Wiesbaden : Springer Spektrum, 2016.
Series: BestMasters.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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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.

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Genre/Form: Electronic books
Additional Physical Format: Print version:
Kroiss, Manuel.
Predicting the Lineage Choice of Hematopoietic Stem Cells : A Novel Approach Using Deep Neural Networks.
Wiesbaden : Springer Fachmedien Wiesbaden, ©2016
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Manuel Kroiss
ISBN: 9783658128791 3658128798 365812878X 9783658128784
OCLC Number: 949884288
Description: 1 online resource (xv, 68 pages).
Contents: Machine Learning --
Deep Learning --
Training Neural Networks --
Recurrent Neural Networks --
Stem Cell Classification Using Microscopy Images.
Series Title: BestMasters.
Responsibility: Manuel Kroiss.

Abstract:

Manuel Kroiss examines the differentiation of hematopoietic stem cells using machine learning methods. With his method, Manuel Kroiss considerably outperforms standard machine learning methods  Read more...

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