Work

Learning classification models of cognitive conditions from subtle behaviors in the digital Clock Drawing Test

Year: 2015

Type: article

Source: Machine Learning

DOI: 10.1007/s10994-015-5529-5

Authors: William Souillard-Mandar, Randall Davis, Cynthia Rudin, Rhoda Au, David J. Libon, Rodney Swenson, Catherine C. Price, Melissa Lamar, Dana L. Penney

Institutions: MIT Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Boston University, Drexel University, University of North Dakota, University of Florida, University of Illinois Chicago, Lahey Hospital and Medical Center

Language: English

Topic: Dementia and Cognitive Impairment Research

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: National Science Foundation, National Institutes of Health, Defense Advanced Research Projects Agency, Advanced Research Projects Agency, National Institute on Aging, National Heart, Lung, and Blood Institute, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Center for Advancing Translational Sciences

Awards: G1490530680, Together: Transforming and Translating Discovery to Improve Health, G2174383782, G232440474, G250621538, G2791745117, G285886997, SCH: EXP: Collaborative Research: THink - Inferring Cognitive State From Subtle Behaviors, G3345260134, G36433118, UF Clinical and Translational Science Award, G5164707915, G5428186612, MRI, Cognitive, Genetic and Biomarker Precursors of AD & Dementia in Young Adults, MRI, Genetics & Cognitive Precursors of AD and Dementia, The Framingham Heart Study, Cortical/Subcortical Circuits in Late-Life Depression

OpenAlex ID: W2177693422

FWCI: 5.293

Cites: 58

Cited by: 163

Related to: 10