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

-15% su kodu: ENG15
71,98 
Įprasta kaina: 84,68 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
71,98 
Įprasta kaina: 84,68 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 84.6800 InStock
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Knygos aprašymas

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.

Informacija

Autorius: Manuel Kroiss
Serija: BestMasters
Leidėjas: Springer Fachmedien Wiesbaden
Išleidimo metai: 2016
Knygos puslapių skaičius: 84
ISBN-10: 365812878X
ISBN-13: 9783658128784
Formatas: 210 x 148 x 6 mm. Knyga minkštu viršeliu
Kalba: Anglų

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