IMPROVING MACHINE LEARNING CLASSIFICATION OF ADHD USING GENE SET POLYGENIC RISK SCORES AND RISK SCORES FROM GENETICALLY CORRELATED PHENOTYPES

被引：0
|
作者：
Barnett, Eric J. [1 ]
Zhang-James, Yanli [1 ]
Faraone, Stephen V. [1 ]
机构：
[1] SUNY Upstate Med Univ, Syracuse, NY 13210 USA
来源：
JOURNAL OF THE AMERICAN ACADEMY OF CHILD AND ADOLESCENT PSYCHIATRY | 2023年 / 62卷 / 10期
关键词：
D O I：
10.1016/j.jaac.2023.07.923
中图分类号：
B844 [发展心理学（人类心理学）];
学科分类号：
040202 ;
摘要：
52.4
引用
收藏
页码：S406 / S406
页数：1
相关论文
共 50 条
  • [1] IMPROVING MACHINE LEARNING PREDICTION OF ADHD USING GENE SET POLYGENIC RISK SCORES AND RISK SCORES FROM GENETICALLY CORRELATED DISORDERS
    Faraone, Stephen V.
    JOURNAL OF THE AMERICAN ACADEMY OF CHILD AND ADOLESCENT PSYCHIATRY, 2021, 60 (10): : S303 - S303
  • [2] PRSET: GENE-SET ANALYSES USING POLYGENIC RISK SCORES
    O'Reilly, Paul
    Ruan, Yunfeng
    Choi, Shing Wan
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2019, 29 : 1126 - 1126
  • [3] Predicting ADHD in alcohol dependence using polygenic risk scores for ADHD
    Patel, Kejal H. S.
    Walters, G. Bragi
    Stefansson, Hreinn
    Stefansson, Kari
    Degenhardt, Franziska
    Nothen, Markus
    Van Der Veen, Tracey
    Demontis, Ditte
    Borglum, Anders
    Kristiansen, Mark
    Bass, Nicholas J.
    McQuillin, Andrew
    AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS, 2024, 195 (04)
  • [4] Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores
    Hrytsenko, Yana
    Shea, Benjamin
    Elgart, Michael
    Kurniansyah, Nuzulul
    Lyons, Genevieve
    Morrison, Alanna C.
    Carson, April P.
    Haring, Bernhard
    Mitchell, Braxton D.
    Psaty, Bruce M.
    Jaeger, Byron C.
    Gu, C. Charles
    Kooperberg, Charles
    Levy, Daniel
    Lloyd-Jones, Donald
    Choi, Eunhee
    Brody, Jennifer A.
    Smith, Jennifer A.
    Rotter, Jerome I.
    Moll, Matthew
    Fornage, Myriam
    Simon, Noah
    Castaldi, Peter
    Casanova, Ramon
    Chung, Ren-Hua
    Kaplan, Robert
    Loos, Ruth J. F.
    Kardia, Sharon L. R.
    Rich, Stephen S.
    Redline, Susan
    Kelly, Tanika
    O'Connor, Timothy
    Zhao, Wei
    Kim, Wonji
    Guo, Xiuqing
    Ida Chen, Yii-Der
    Trans Omics Precision Med Consortium
    Sofer, Tamar
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [5] INVESTIGATION OF PATHWAY-BASED POLYGENIC RISK SCORES USING MACHINE LEARNING PREDICTION AND CLASSIFICATION SCHEMES
    Panagiotaropoulou, Georgia
    Ripke, Stephan
    Baker, Emily
    Escott-Price, Valentina
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2019, 29 : S229 - S230
  • [6] Polygenic risk scores and machine learning improve glaucoma prediction
    Gao, Xiaoyi Raymond
    Lin, Yizi
    Chiariglione, Marion
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2021, 62 (08)
  • [7] POLYGENIC RISK SCORES FOR ADHD AND TREATMENT RESPONSE TO METHYLPHENIDATE
    da Cunha, Pamela Ferreira
    Machado, Guilherme
    Bandeira, Cibele Edom
    Tavares, Maria Eduarda
    Rovaris, Diego Luiz
    Vitor, Marcelo
    Grevet, Eugenio H.
    Bau, Claiton H. D.
    da Silva, Bruna Santos
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2021, 51 : E229 - E229
  • [8] Polygenic Risk Scores and Genetically Complex Eye Disease
    Le, Ngoc-Quynh
    He, Weixiong
    MacGregor, Stuart
    ANNUAL REVIEW OF VISION SCIENCE, 2024, 10 : 403 - 423
  • [9] Polygenic Risk Scores and Hearing Loss Phenotypes in Children
    Wang, Jing
    He, Fan
    Shepherd, Daisy A.
    Li, Shuai
    Lange, Katherine
    Sung, Valerie
    Morgan, Angela
    Kerr, Jessica A.
    Saffery, Richard
    Wake, Melissa
    JAMA OTOLARYNGOLOGY-HEAD & NECK SURGERY, 2025, 151 (01) : 56 - 64
  • [10] PATHWAY-BASED POLYGENIC RISK SCORES USING MACHINE LEARNING CLASSIFICATION SCHEMES: APPLICATION TO BIPOLAR DISORDER
    Panagiotaropoulou, Georgia
    Chen, Junfang
    Ripke, Stephan
    EUROPEAN NEUROPSYCHOPHARMACOLOGY, 2021, 51 : E205 - E205
12345