Speech‐based machine learning for early Alzheimer's phenotypes classification: Predicting both clinical diagnosis and underlying pathology at onset time

Speech-based classification provides valuable early prognostic insights by linking clinical phenotypes with CSF profiles at onset time. By enhancing prognostic precision, such tools could improve early intervention strategies to counter disease progression. However, larger studies and advanced classification approaches are essential to confirm these findings and validate speech classification as a reliable, non-invasive tool for early differential prognosis.