Causal Discovery from a Mixture of Experimental and Observational Data

从实验和观察数据的混合中发现因果关系

基本信息

  • 批准号:
    9812021
  • 负责人:
  • 金额:
    $ 25.49万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    1998
  • 资助国家:
    美国
  • 起止时间:
    1998-09-01 至 2002-09-30
  • 项目状态:
    已结题

项目摘要

Causal knowledge makes up much of what we know and want to know in science. The goal of this research is to develop and apply a unified method for representing and discovering causal relationships from a mixture of observational and experimental data. Probabilistic causal networks are being used as a representation of causality. Bayesian methods are being applied to learn probabilistic causal networks from data. A computer implementation of the discovery method is being investigated empirically using data generated from existing causal models that were constructed by human experts. The ability to use a mixture of observational and experimental data will expand considerably the scope of application of Bayesian causal modeling and discovery in science. http://www.cbmi.upmc.edu/~gfc/index.html/causal_discovery
在科学中,因果知识构成了我们所知道和想知道的大部分知识。本研究的目标是开发和应用一种统一的方法,从观察和实验数据的混合中表示和发现因果关系。概率因果网络被用来表示因果关系。贝叶斯方法正被应用于从数据中学习概率因果网络。发现方法的计算机实现正在使用由人类专家构建的现有因果模型生成的数据进行实证研究。混合使用观测和实验数据的能力将大大扩展贝叶斯因果模型和科学发现的应用范围。http://www.cbmi.upmc.edu/~gfc/index.html/causal_discovery

项目成果

期刊论文数量(0)
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Gregory Cooper其他文献

Thialfi: a client notification service for internet-scale applications
Thialfi:适用于互联网规模应用程序的客户端通知服务
LUMEN-APPOSING METAL STENT IN THE MANAGEMENT OF BENIGN GASTROINTESTINAL STRICTURES: A SYSTEMATIC REVIEW AND META-ANALYSIS
腔内贴壁金属支架在良性胃肠道狭窄治疗中的应用:系统评价和荟萃分析
  • DOI:
    10.1016/j.gie.2023.04.1842
  • 发表时间:
    2023-06-01
  • 期刊:
  • 影响因子:
    7.500
  • 作者:
    Rami Musallam;Wael Al-Yaman;Azizullah Beran;Babu Mohan;Motib Alabdulwahhab;Emad Mansoor;Naresh Gunaratnam;Gregory Cooper;Roberto Simons-Linares;Amitabh Chak;Prabhleen Chahal;Mohannad Abousaleh
  • 通讯作者:
    Mohannad Abousaleh
eP144: Long-read genome sequencing secondary processing pipelines provide variant call accuracy that exceeds current clinical standards for short-read genome sequencing
  • DOI:
    10.1016/j.gim.2022.01.180
  • 发表时间:
    2022-03-01
  • 期刊:
  • 影响因子:
  • 作者:
    James Holt;Lori Handley;James Lawlor;Susan Hiatt;Gregory Cooper;Jane Grimwood;Ghunwa Nakouzi
  • 通讯作者:
    Ghunwa Nakouzi
eP494: Integration of genomics into primary care via the Alabama Genomic Health Initiative
  • DOI:
    10.1016/j.gim.2022.01.526
  • 发表时间:
    2022-03-01
  • 期刊:
  • 影响因子:
  • 作者:
    Bruce Korf;Devin Absher;Irfan Asif;Lori Bateman;Gregory Barsh;Kevin Bowling;Gregory Cooper;Brittney Davis;Kelly East;Candice Finnila;Blake Goff;Melissa Kelly;Whitley Kelley;Donald Latner;James Lawlor;Nita Limdi;Thomas May;Matthew Might;Irene Moss;Mariko Nakano
  • 通讯作者:
    Mariko Nakano
P134 PREVALENCE OF LACTOSE INTOLERANCE IN INFLAMMATORY BOWEL DISEASE IN THE UNITED STATES BETWEEN 2014 AND 2019: A POPULATION-BASED STUDY
  • DOI:
    10.1053/j.gastro.2019.11.126
  • 发表时间:
    2020-02-01
  • 期刊:
  • 影响因子:
  • 作者:
    Emad Mansoor;Mohannad Abou-Saleh;Muhammad Talal Sarmini;Vijit Chouhan;Miguel Regueiro;Jeffry Katz;Gregory Cooper
  • 通讯作者:
    Gregory Cooper

Gregory Cooper的其他文献

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{{ truncateString('Gregory Cooper', 18)}}的其他基金

BD Spokes: SPOKE: NORTHEAST: Collaborative Research: Integration of Environmental Factors and Causal Reasoning Approaches for Large-Scale Observational Health Research
BD 发言:发言:东北:合作研究:大规模观察健康研究的环境因素和因果推理方法的整合
  • 批准号:
    1636786
  • 财政年份:
    2017
  • 资助金额:
    $ 25.49万
  • 项目类别:
    Standard Grant
ITR: Bayesian Modeling for Biosurveillance
ITR:生物监测贝叶斯建模
  • 批准号:
    0325581
  • 财政年份:
    2003
  • 资助金额:
    $ 25.49万
  • 项目类别:
    Continuing Grant
Learning Bayesian Networks that Contain Both Discrete and Continuous Variables
学习包含离散变量和连续变量的贝叶斯网络
  • 批准号:
    9509792
  • 财政年份:
    1995
  • 资助金额:
    $ 25.49万
  • 项目类别:
    Continuing Grant
Improving the Cost Effectiveness of Health Care Through Machine Learning Applied to Large Clinical Databases
通过应用于大型临床数据库的机器学习提高医疗保健的成本效益
  • 批准号:
    9315428
  • 财政年份:
    1994
  • 资助金额:
    $ 25.49万
  • 项目类别:
    Continuing Grant
Learning Probabilistic Networks from Databases
从数据库学习概率网络
  • 批准号:
    9111590
  • 财政年份:
    1991
  • 资助金额:
    $ 25.49万
  • 项目类别:
    Continuing Grant

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