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5min chapter
AI & ADHD Support: Interview with Tobie Langel
The ADHD Skills Lab
Machine Learning Applications in Diagnosing ADHD
The chapter delves into a specific paper analyzing the accuracy and sensitivity of machine learning models using MRI, FMRI, EEG, and genetic data to predict ADHD cases, highlighting a range of 69 to 96% sensitivity. It compares the effectiveness of DSM criteria with machine learning algorithms and examines the pattern matching capabilities of machine learning for creating diagnostic models.
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