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Genetic Architecture, Polygenic Risk Scores, and Artificial Intelligence Guided Risk Stratification in Congenital Long Qt Syndrome
Genetic Architecture, Polygenic Risk Scores, and Artificial Intelligence Guided Risk Strat...
Genetic Architecture, Polygenic Risk Scores, and Artificial Intelligence Guided Risk Stratification in Congenital Long Qt Syndrome

Detailed Information

자료유형  
 학위논문파일 국외
ISBN  
9798535568324
DDC  
575
저자명  
Turkowski, Kari Leah.
서명/저자  
Genetic Architecture, Polygenic Risk Scores, and Artificial Intelligence Guided Risk Stratification in Congenital Long Qt Syndrome
발행사항  
[Sl] : College of Medicine - Mayo Clinic, 2020
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2020
형태사항  
352 p
주기사항  
Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
주기사항  
Advisor: Ackerman, Michael J.
학위논문주기  
Thesis (Ph.D.)--College of Medicine - Mayo Clinic, 2020.
사용제한주기  
This item must not be sold to any third party vendors.
일반주제명  
Genetics
일반주제명  
Artificial intelligence
일반주제명  
Public health
일반주제명  
Individual & family studies
일반주제명  
Computer science
일반주제명  
Health sciences
키워드  
Congenital heart disease
키워드  
Genome-Wide Association Studies
키워드  
Long QT Syndrome
키워드  
Machine learning
키워드  
Polygenic risk score
키워드  
Genetic architecture
키워드  
Risk stratification
키워드  
Ion channel disease
키워드  
Congenital diseases
기타저자  
College of Medicine - Mayo Clinic Clinical and Translational Science
기본자료저록  
Dissertations Abstracts International. 83-03B.
기본자료저록  
Dissertation Abstract International
전자적 위치 및 접속  
로그인 후 원문을 볼 수 있습니다.

MARC

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■035    ▼a(MiAaPQ)AAI28086646
■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a575
■1001  ▼aTurkowski,  Kari  Leah.
■24510▼aGenetic  Architecture,  Polygenic  Risk  Scores,  and  Artificial  Intelligence  Guided  Risk  Stratification  in  Congenital  Long  Qt  Syndrome
■260    ▼a[Sl]▼bCollege  of  Medicine  -  Mayo  Clinic▼c2020
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2020
■300    ▼a352  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  83-03,  Section:  B.
■500    ▼aAdvisor:  Ackerman,  Michael  J.
■5021  ▼aThesis  (Ph.D.)--College  of  Medicine  -  Mayo  Clinic,  2020.
■506    ▼aThis  item  must  not  be  sold  to  any  third  party  vendors.
■590    ▼aSchool  code:  1542.
■650  4▼aGenetics
■650  4▼aArtificial  intelligence
■650  4▼aPublic  health
■650  4▼aIndividual  &  family  studies
■650  4▼aComputer  science
■650  4▼aHealth  sciences
■653    ▼aCongenital  heart  disease
■653    ▼aGenome-Wide  Association  Studies
■653    ▼aLong  QT  Syndrome
■653    ▼aMachine  learning
■653    ▼aPolygenic  risk  score
■653    ▼aGenetic  architecture
■653    ▼aRisk  stratification
■653    ▼aIon  channel  disease
■653    ▼aCongenital  diseases
■690    ▼a0369
■690    ▼a0800
■690    ▼a0984
■690    ▼a0566
■690    ▼a0628
■690    ▼a0573
■71020▼aCollege  of  Medicine  -  Mayo  Clinic▼bClinical  and  Translational  Science.
■7730  ▼tDissertations  Abstracts  International▼g83-03B.
■773    ▼tDissertation  Abstract  International
■790    ▼a1542
■791    ▼aPh.D.
■792    ▼a2020
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16051028▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.
■980    ▼a202202▼f2022

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