Robust ADHD testing by applying clustering techniques to survey responses or speech data

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.