Novel data-driven approach improves classification of post-stroke aphasia subtypes

Takeaway

  • A community detection analysis represents a novel method for classification of post-stroke aphasia subtypes.

Why this matters

  • Aphasia is a language impairment which often occurs after left hemisphere stroke.

  • These novel findings demonstrate the feasibility of applying machine learning and data-driven techniques in the study of aphasia compared with current standard tools. Facilitating data sharing between investigators and clinicians will further our understanding of neurological impairments and improve prognosis for people with post-stroke aphasia.