AI & Machine Learning in ADHD Diagnosis

Plain-language summary

Research suggests that AI and machine learning could potentially make ADHD diagnosis more accurate and efficient. Several studies show promising results in using these technologies, sometimes in combination with other tools like smartphone assessments or wearable devices. However, it's important to remember that this is a developing field, and more research is needed to confirm these findings and address areas where evidence might still be limited or mixed.

Key findings

• AI and machine learning models are being developed to predict ADHD, even using data from smartphone-based cognitive tests.
• Scientists are working on creating AI tools that can diagnose ADHD fairly, ensuring they don't show bias based on gender.
• Combining "explainable AI" with clinical information can help doctors better understand and diagnose ADHD.
• Wearable devices that measure brain activity (like EEGs) along with behavior can help diagnose ADHD in young children.
• AI is being explored in clinical settings in the UK to help diagnose ADHD, showing the real-world application of this technology.

Studies cited (5)

1. Machine learning on a smartphone-based CPT for ADHD prediction — Casals N, Larsson S, Hansen M (2025, Frontiers in psychiatry, other)

   DOI: 10.3389/fpsyt.2025.1564351 PMCID: PMC12634579

2. Toward a fair, gender-debiased classifier for the diagnosis of attention deficit/hyperactivity disorder- a Machine-Learning based classification study — Neufang S, Li F, Akhrif A (2025, BMC medical informatics and decision making, other)

   DOI: 10.1186/s12911-025-03126-0 PMCID: PMC12326834

3. Integrating explainable AI with clinical features to enhance ADHD diagnostic understanding — Shakeel HM, Antoniou G, Adamou M (2025, Frontiers in psychiatry, other)

   DOI: 10.3389/fpsyt.2025.1706216 PMCID: PMC12690393

4. The utility of wearable electroencephalography combined with behavioral measures to establish a practical multi-domain model for facilitating the diagnosis of young children with attention-deficit/hyperactivity disorder — Chen IC, Chang CL, Chang MH (2024, Journal of neurodevelopmental disorders, other)

   DOI: 10.1186/s11689-024-09578-1 PMCID: PMC11552361

5. Diagnosing attention-deficit hyperactivity disorder (ADHD) using artificial intelligence: a clinical study in the UK — Chen T, Tachmazidis I, Batsakis S (2023, Frontiers in psychiatry, other)

   DOI: 10.3389/fpsyt.2023.1164433 PMCID: PMC10288489