Assessing machine learning for fair prediction of ADHD in school pupils using a retrospective cohort study of linked education and healthcare data

Lucile Ter-Minassian; Natalia Viani; Alice Wickersham; Lauren Cross; Robert Stewart; Sumithra Velupillai; Johnny Downs

Assessing machine learning for fair prediction of ADHD in school pupils using a retrospective cohort study of linked education and healthcare data

Lucile Ter-Minassian, Natalia Viani, Alice Wickersham, Lauren Cross, Robert Stewart, Sumithra Velupillai, Johnny Downs

King's College London

Research output: Contribution to journal › Article › peer-review

Original language	English
Journal	BMJ Open
Publication status	Accepted/In press - 8 Aug 2022

Cite this

@article{27dd451323fa43ccbdc5839407260fcb,

title = "Assessing machine learning for fair prediction of ADHD in school pupils using a retrospective cohort study of linked education and healthcare data",

author = "Lucile Ter-Minassian and Natalia Viani and Alice Wickersham and Lauren Cross and Robert Stewart and Sumithra Velupillai and Johnny Downs",

year = "2022",

month = aug,

day = "8",

language = "English",

journal = "BMJ Open",

issn = "2044-6055",

publisher = "BMJ Publishing Group",

}

TY - JOUR

T1 - Assessing machine learning for fair prediction of ADHD in school pupils using a retrospective cohort study of linked education and healthcare data

AU - Ter-Minassian, Lucile

AU - Viani, Natalia

AU - Wickersham, Alice

AU - Cross, Lauren

AU - Stewart, Robert

AU - Velupillai, Sumithra

AU - Downs, Johnny

PY - 2022/8/8

Y1 - 2022/8/8

M3 - Article

SN - 2044-6055

JO - BMJ Open

JF - BMJ Open

ER -