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Analyzing the Multidimensionality of Aging by Using Machine Learning to Predict Age from Diverse Medical Datasets
Analyzing the Multidimensionality of Aging by Using Machine Learning to Predict Age from D...
Contents Info
Analyzing the Multidimensionality of Aging by Using Machine Learning to Predict Age from Diverse Medical Datasets
Material Type  
 단행본
ISBN  
9798534681314
DDC  
574
Author  
Le Goallec, Alan.
Title/Author  
Analyzing the Multidimensionality of Aging by Using Machine Learning to Predict Age from Diverse Medical Datasets
Publish Info  
[Sl] : Harvard University, 2021
Publish Info  
Ann Arbor : ProQuest Dissertations & Theses, 2021
Material Info  
457 p
General Note  
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
General Note  
Includes supplementary digital materials.
General Note  
Advisor: Patel, Chirag J.
학위논문주기  
Thesis (Ph.D.)--Harvard University, 2021.
Restrictions on Access Note  
This item must not be sold to any third party vendors.
Subject Added Entry-Topical Term  
Bioinformatics
Subject Added Entry-Topical Term  
Artificial intelligence
Subject Added Entry-Topical Term  
Statistics
Subject Added Entry-Topical Term  
DNA methylation
Subject Added Entry-Topical Term  
Datasets
Subject Added Entry-Topical Term  
X rays
Subject Added Entry-Topical Term  
Neural networks
Subject Added Entry-Topical Term  
Electrocardiography
Index Term-Uncontrolled  
Aging
Index Term-Uncontrolled  
Artificial intelligence
Index Term-Uncontrolled  
Data science
Index Term-Uncontrolled  
Deep learning
Index Term-Uncontrolled  
Genetics
Index Term-Uncontrolled  
Machine learning
Added Entry-Corporate Name  
Harvard University Systems Biology
Host Item Entry  
Dissertations Abstracts International. 83-02B.
Host Item Entry  
Dissertation Abstract International
Electronic Location and Access  
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소장사항  
202202 2022
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