Genetic algorithm with logistic regression for prediction of progression to Alzheimer's disease

被引：0
|
作者：
Piers Johnson
Luke Vandewater
William Wilson
Paul Maruff
Greg Savage
Petra Graham
Lance S Macaulay
Kathryn A Ellis
Cassandra Szoeke
Ralph N Martins
Christopher C Rowe
Colin L Masters
David Ames
Ping Zhang
机构：
[1] CSIRO,Digital Productivity Flagship
[2] The Florey Institute of Neuroscience and Mental Health,ARC Centre of Excellence in Cognition and its Disorders, and Department of Psychology
[3] CogState Ltd,Department of Statistics, Faculty of Science
[4] Macquarie University,Food and Nutrition Flagship
[5] Macquarie University,Academic Unit for Psychiatry of Old Age, Department of Psychiatry
[6] CSIRO,School of Exercise Biomedical and Health Sciences
[7] The University of Melbourne,Department of Nuclear Medicine & Centre for PET
[8] Mental Health Research Institute,Department of Medicine
[9] Edith Cowan University,Department of Pathology
[10] Sir James McCusker Alzheimer's Disease Research Unit,undefined
[11] Austin Health,undefined
[12] Melbourne,undefined
[13] University of Melbourne,undefined
[14] The University of Melbourne,undefined
[15] National Ageing Research Institute,undefined
[16] CRC for Mental Health,undefined
来源：
BMC Bioinformatics | / 15卷
关键词：
Genetic Algorithm; Mild Cognitive Impairment; Monte Carlo; Clinical Dementia Rate; Semantic Fluency;
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] Genetic algorithm with logistic regression for prediction of progression to Alzheimer's disease
    Johnson, Piers
    Vandewater, Luke
    Wilson, William
    Maruff, Paul
    Savage, Greg
    Graham, Petra
    Macaulay, Lance S.
    Ellis, Kathryn A.
    Szoeke, Cassandra
    Martins, Ralph N.
    Rowe, Christopher C.
    Masters, Colin L.
    Ames, David
    Zhang, Ping
    BMC BIOINFORMATICS, 2014, 15
  • [2] Genetic algorithm with logistic regression feature selection for Alzheimer's disease classification
    Divya, R.
    Kumari, R. Shantha Selva
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (14) : 8435 - 8444
  • [3] Diagnosis of Alzheimer's disease based on logistic regression algorithm
    Chen, Yusi
    Liu, Ning
    Chen, PeiKun
    2022 INTERNATIONAL CONFERENCE ON COMPUTING, ROBOTICS AND SYSTEM SCIENCES, ICRSS, 2022, : 64 - 67
  • [4] An adaptive genetic algorithm for selection of blood-based biomarkers for prediction of Alzheimer's disease progression
    Vandewater, Luke
    Brusic, Vladimir
    Wilson, William
    Macaulay, Lance
    Zhang, Ping
    BMC BIOINFORMATICS, 2015, 16
  • [5] Predicting Progression of Alzheimer's Disease Using Ordinal Regression
    Doyle, Orla M.
    Westman, Eric
    Marquand, Andre F.
    Mecocci, Patrizia
    Vellas, Bruno
    Tsolaki, Magda
    Kloszewska, Iwona
    Soininen, Hilkka
    Lovestone, Simon
    Williams, Steve C. R.
    Simmons, Andrew
    PLOS ONE, 2014, 9 (08):
  • [6] Logistic Regression and Logistic Regression-Genetic Algorithm for Classification of Liver Cancer Data
    Wibowo, Velery Virgina Putri
    Rustam, Zuherman
    Laeli, Afifah Rofi
    Said, Alva Andhika
    2021 INTERNATIONAL CONFERENCE ON DECISION AID SCIENCES AND APPLICATION (DASA), 2021,
  • [7] Early diagnosis model of Alzheimer's Disease based on sparse logistic regression
    Xiao, Ruyi
    Cui, Xinchun
    Qiao, Hong
    Zheng, Xiangwei
    Zhang, Yiquan
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (03) : 3969 - 3980
  • [8] Early diagnosis model of Alzheimer’s Disease based on sparse logistic regression
    Ruyi Xiao
    Xinchun Cui
    Hong Qiao
    Xiangwei Zheng
    Yiquan Zhang
    Multimedia Tools and Applications, 2021, 80 : 3969 - 3980
  • [9] Visual tracking with genetic algorithm augmented logistic regression
    Lei Qu
    Guoqiang Zhao
    Baochen Yao
    Yuzhen Li
    Signal, Image and Video Processing, 2018, 12 : 33 - 40
  • [10] Visual tracking with genetic algorithm augmented logistic regression
    Qu, Lei
    Zhao, Guoqiang
    Yao, Baochen
    Li, Yuzhen
    SIGNAL IMAGE AND VIDEO PROCESSING, 2018, 12 (01) : 33 - 40
12345