Artificial intelligence as a support to diagnose ADHD: an insight of unorthodox approaches: a scoping review

Learning Objectives:

1. Identify and describe at least five different AI-based modalities used for ADHD diagnosis.

2. Evaluate the clinical challenges and limitations of implementing AI-based ADHD diagnostic tools in practice, including issues of algorithmic bias, data quality inconsistencies, the need for large diverse datasets, lack of standardized evaluation metrics, and the “black box” nature of deep learning models that affects clinical transparency and decision-making.

Zaheer, A., & Akhtar, A. (2025). Artificial intelligence as a support to diagnose ADHD: an insight of unorthodox approaches: a scoping review. Child Neuropsychology, 1–35. https://doi.org/10.1080/09297049.2025.2468411

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