Fig. 4: Schematic representation of the three approaches for the ON/OFF medication state classification of speech recordings. | npj Parkinson's Disease

Fig. 4: Schematic representation of the three approaches for the ON/OFF medication state classification of speech recordings.

From: Detecting neuropsychiatric fluctuations in Parkinson’s Disease using patients’ own words: the potential of large language models

Fig. 4

The English transcription of each speech recording was the input for all the approaches. a The transcriptions (query) and the 20 items (corpus) of the Neuropsychiatric Fluctuation Scale (NFS) are first mapped into numerical vectors. Each recording transcription is treated as a query, and the five most similar NFS items are retrieved using cosine similarity. The query is then classified based on the most frequent label (ON or OFF) among the retrieved items. b The medication state is predicted by applying machine learning (ML) models on linguistic features represented as text embeddings. c English transcriptions are directly included in a decoder-only Large Language Model (LLM) prompt.

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