Two Frameworks for Reliable Machine Learning in Biology and Medicine
Two Frameworks for Reliable Machine Learning in Biology and Medicine
Detailed Information
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20220210094735
- ISBN
- 9798494461896
- DDC
- 300
- 저자명
- Abid, Abubakar.
- 서명/저자
- Two Frameworks for Reliable Machine Learning in Biology and Medicine
- 발행사항
- [Sl] : Stanford University, 2021
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2021
- 형태사항
- 106 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 83-05, Section: B.
- 주기사항
- Advisor: Zou, James.
- 학위논문주기
- Thesis (Ph.D.)--Stanford University, 2021.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 일반주제명
- Patients
- 일반주제명
- Software
- 일반주제명
- Medicine
- 일반주제명
- Deep learning
- 일반주제명
- Collaboration
- 일반주제명
- Sensitivity analysis
- 일반주제명
- Spectrum analysis
- 일반주제명
- Audiences
- 일반주제명
- Ejection fraction
- 일반주제명
- Physicians
- 일반주제명
- Medical research
- 일반주제명
- Biology
- 일반주제명
- Subject specialists
- 일반주제명
- Algorithms
- 일반주제명
- Time series
- 일반주제명
- Feedback
- 일반주제명
- Ultrasonic imaging
- 일반주제명
- Engineers
- 일반주제명
- Interfaces
- 일반주제명
- Acoustics
- 일반주제명
- Analytical chemistry
- 일반주제명
- Artificial intelligence
- 일반주제명
- Chemistry
- 일반주제명
- Computer science
- 일반주제명
- Medical imaging
- 일반주제명
- Medical personnel
- 일반주제명
- Optics
- 기타저자
- Stanford University.
- 기본자료저록
- Dissertations Abstracts International. 83-05B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520220210094735
■020 ▼a9798494461896
■035 ▼a(MiAaPQ)AAI28812876
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a300
■1001 ▼aAbid, Abubakar.
■24510▼aTwo Frameworks for Reliable Machine Learning in Biology and Medicine
■260 ▼a[Sl]▼bStanford University▼c2021
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2021
■300 ▼a106 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 83-05, Section: B.
■500 ▼aAdvisor: Zou, James.
■5021 ▼aThesis (Ph.D.)--Stanford University, 2021.
■506 ▼aThis item must not be sold to any third party vendors.
■590 ▼aSchool code: 0212.
■650 4▼aPatients
■650 4▼aSoftware
■650 4▼aMedicine
■650 4▼aDeep learning
■650 4▼aCollaboration
■650 4▼aSensitivity analysis
■650 4▼aSpectrum analysis
■650 4▼aAudiences
■650 4▼aEjection fraction
■650 4▼aPhysicians
■650 4▼aMedical research
■650 4▼aBiology
■650 4▼aSubject specialists
■650 4▼aAlgorithms
■650 4▼aTime series
■650 4▼aFeedback
■650 4▼aUltrasonic imaging
■650 4▼aEngineers
■650 4▼aInterfaces
■650 4▼aAcoustics
■650 4▼aAnalytical chemistry
■650 4▼aArtificial intelligence
■650 4▼aChemistry
■650 4▼aComputer science
■650 4▼aMedical imaging
■650 4▼aMedical personnel
■650 4▼aOptics
■690 ▼a0564
■690 ▼a0306
■690 ▼a0986
■690 ▼a0486
■690 ▼a0800
■690 ▼a0485
■690 ▼a0984
■690 ▼a0574
■690 ▼a0207
■690 ▼a0752
■71020▼aStanford University.
■7730 ▼tDissertations Abstracts International▼g83-05B.
■773 ▼tDissertation Abstract International
■790 ▼a0212
■791 ▼aPh.D.
■792 ▼a2021
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16055281▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202202▼f2022
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