Sparsifying machine learning models identify stable subsets of predictive features for behavioral detection of autism

被引：0
|
作者：
Sebastien Levy
Marlena Duda
Nick Haber
Dennis P. Wall
机构：
[1] Stanford University,Department of Pediatrics, Division of Systems Medicine
[2] Stanford University,Department of Biomedical Data Science
[3] Institute for Computational and Mathematical Engineering,undefined
[4] Stanford University,undefined
来源：
Molecular Autism | / 8卷
关键词：
Autism; Autism spectrum disorder; ASD; Autism screening; Autism diagnosis; Machine learning; Sparse machine learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [1] Sparsifying machine learning models identify stable subsets of predictive features for behavioral detection of autism
    Levy, Sebastien
    Duda, Marlena
    Haber, Nick
    Wall, Dennis P.
    MOLECULAR AUTISM, 2017, 8
  • [2] Machine learning models identify predictive features of patient mortality across dementia types
    Zhang, Jimmy
    Song, Luo
    Miller, Zachary
    Chan, Kwun C. G.
    Huang, Kuan-lin
    COMMUNICATIONS MEDICINE, 2024, 4 (01):
  • [3] Machine learning models identify predictive features of patient mortality across dementia types
    Jimmy Zhang
    Luo Song
    Zachary Miller
    Kwun C. G. Chan
    Kuan-lin Huang
    Communications Medicine, 4
  • [4] Applying Machine Learning to Identify Autism With Restricted Kinematic Features
    Zhao, Zhong
    Zhang, Xiaobin
    Li, Wenzhou
    Hu, Xinyao
    Qu, Xingda
    Cao, Xiaolan
    Liu, Yanru
    Lu, Jianping
    IEEE ACCESS, 2019, 7 : 157614 - 157622
  • [5] Selection of Subsets of Ordered Features in Machine Learning
    Seredin, O.
    Kopylov, A.
    Mottl, V.
    MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION, 2009, 5632 : 16 - +
  • [6] RETRACTED: Facial Features Detection System To Identify Children With Autism Spectrum Disorder: Deep Learning Models (Retracted Article)
    Ahmed, Zeyad A. T.
    Aldhyani, Theyazn H. H.
    Jadhav, Mukti E.
    Alzahrani, Mohammed Y.
    Alzahrani, Mohammad Eid
    Althobaiti, Maha M.
    Alassery, Fawaz
    Alshaflut, Ahmed
    Alzahrani, Nouf Matar
    Al-madani, Ali Mansour
    COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2022, 2022
  • [7] MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE METHODS TO IDENTIFY CLINICAL FEATURES PREDICTIVE OF PROGRESSIVE MAFLD
    Salvati, Antonio
    De Rosa, Laura
    Salvati, Nicola
    Faita, Francesco
    Cavallone, Daniela
    Ricco, Gabriele
    Colombatto, Piero
    Coco, Barbara
    Romagnoli, Veronica
    Oliveri, Filippo
    Bonino, Ferruccio
    Brunetto, Maurizia R.
    HEPATOLOGY, 2021, 74 : 963A - 963A
  • [8] MACHINE LEARNING-BASED PREDICTIVE MODELS OF BEHAVIORAL AND PSYCHOLOGICAL SYMPTOMS OF DEMENTIA
    Cho, Eunhee
    Kim, Sujin
    Heo, Seok-Jae
    Shin, Jinhee
    Ye, Byoung Seok
    Lee, Jun Hong
    Kang, Bada
    INNOVATION IN AGING, 2021, 5 : 645 - 645
  • [9] Machine Learning-Based Predictive Models for Detection of Cardiovascular Diseases
    Ogunpola, Adedayo
    Saeed, Faisal
    Basurra, Shadi
    Albarrak, Abdullah M.
    Qasem, Sultan Noman
    DIAGNOSTICS, 2024, 14 (02)
  • [10] Identifying neuroanatomical and behavioral features for autism spectrum disorder diagnosis in children using machine learning
    Han, Yu
    Rizzo, Donna M.
    Hanley, John P.
    Coderre, Emily L.
    Prelock, Patricia A.
    PLOS ONE, 2022, 17 (07):
12345