Cluster Newton Method for Underdetermined Inverse Problems and its Application to Pharmacokinetics Model
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- Aoki Yasunori
- Uppsala Universitet薬学部Pharmaceutical Bioscience学科
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- Hayami Ken
- 国立情報学研究所:総合研究大学院大学
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- Konagaya Akihiko
- 東京工業大学大学院知能システム科学専攻
Bibliographic Information
- Other Title
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- 劣決定逆問題に対するCluster Newton法とその薬物動態モデルへの応用
- レツケッテイ ギャクモンダイ ニ タイスル Cluster Newtonホウ ト ソノ ヤクブツ ドウタイ モデル エ ノ オウヨウ
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Abstract
As the observations we can make from patients are limited compared to the complexity of the physiology, underdetermined inverse problems appear often in the parameter estimation problems of physiologically based pharmacokinetics (PBPK) models. We address this issues of not being able to identify the model parameter set uniquely by finding multiple sets of possible parameter sets that are consistent with the observations. As this approach requires multiple parameter estimations of a complex model, the computational cost can be a bottle neck. In this paper, we introduce a new computationally efficient algorithm called the Cluster Newton method to find multiple solutions of an underdetermined inverse problem.
Journal
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- Bulletin of the Japan Society for Industrial and Applied Mathematics
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Bulletin of the Japan Society for Industrial and Applied Mathematics 24 (4), 151-159, 2014
The Japan Society for Industrial and Applied Mathematics
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Details 詳細情報について
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- CRID
- 1390001205765575936
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- NII Article ID
- 110009900558
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- NII Book ID
- AN10288886
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- ISSN
- 09172270
- 24321982
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- NDL BIB ID
- 026010808
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed