Existing tests for attention deficit hyperactivity disorder (ADHD) may exhibit some bias. Also, these tests require filling in a survey with subjective responses, which can lead to misdiagnosis. The techniques described herein reduce bias in ADHD tests by seeking clusters in test-parameter space conditioned on certain characteristics of a person. Clustering is performed using machine learning techniques. With user permission, speech data is obtained via one or more devices such as a phone, smart speaker, etc. an is used to make objective diagnoses of ADHD.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.