Development of a predicting system for children with ADHD
| Project/Area Number |
15H05405
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| Research Category |
Grant-in-Aid for Young Scientists (A)
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| Allocation Type | Single-year Grants |
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| Research Field |
Special needs education
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| Research Institution | National Center of Neurology and Psychiatry |
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Principal Investigator |
yasumura akira 国立研究開発法人国立精神・神経医療研究センター, 精神保健研究所 知的障害研究部, 研究生 (60723468)
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| Research Collaborator |
INAGAKI Masumi
NAKAGAWA Eiji
YAMASHITA Yushiro
AIHARA Masao
MIYAJIMA Tasuku
OMORI Mikimasa
FUKUDA Ayako
TACHIMORI Hisateru
YASUMURA Yukiko
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
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| Keywords | 発達障害 / ADHD / 機械学習 / 抑制機能 / 前頭前野 / 小児 / 診断補助 / バイオマーカー / 脳機能 / 脳機能計測 / 近赤外分光法 |
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| Outline of Final Research Achievements |
The researchers devised a method to predict the severity of children with attention deficit / hyperactivity disorder (ADHD) among developmental disorders using brain function measurement, and have applied for international patent (US). Then, in order to search for ADHD biomarkers, the diagnostic prediction accuracy was examined by applying machine learning to behavior during inhibition task and frontal cerebral blood flow dynamics. As a result, accuracy of sensitivity 88.7%, specificity 83.8%, area under the receiver operation characteristic curve 0.90 was obtained. It was shown that the evaluation method of restraint task using machine learning has high utility as diagnostic aid for children with ADHD. Research results were published in international scientific journals.
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Report
(4 results)
Research Products
(8 results)
