Dataset variable summary.

<div><p>Signs and symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD) are present at preschool ages and often not identified for early intervention. We aimed to use machine learning to detect ADHD early among kindergarten-aged children using population-level administrative health...

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Main Author:	Yang S. Liu (10355988) (author)
Other Authors:	Fernanda Talarico (807333) (author), Dan Metes (13168852) (author), Yipeng Song (1471063) (author), Mengzhe Wang (1518892) (author), Lawrence Kiyang (13168849) (author), Dori Wearmouth (17332793) (author), Shelly Vik (11632163) (author), Yifeng Wei (1324362) (author), Yanbo Zhang (184664) (author), Jake Hayward (2618986) (author), Ghalib Ahmed (14146800) (author), Ashley Gaskin (15259678) (author), Russell Greiner (6063) (author), Andrew Greenshaw (6197054) (author), Alex Alexander (6633185) (author), Magdalena Janus (5857538) (author), Bo Cao (552407) (author)
Published:	2024
Subjects:	Medicine Cell Biology Neuroscience Biotechnology Developmental Biology Science Policy Mental Health Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> signs study cohort consists machine learning algorithms use machine learning predict adhd prospectively early development instrument 494 children born adhd )</ p use population early intervention early identification year follow valuable tool socioeconomic status preschool ages hyperactivity disorder findings suggest edi ). attended kindergarten 680 children 2016 without
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Dataset variable summary.

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