| 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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| 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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