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Automated classification of primary progressive aphasia subtypes from narrative speech transcripts
Fraser KC, Meltzer JA, Graham NL, Leonard C, Hirst G, Black SE, Rochon E.. Cortex; a journal devoted to the study of the nervous system and behavior, 2012-12-21
Topic: Risk, prevention and care in population studies
In the early stages of neurodegenerative disorders, individuals may exhibit a decline in language abilities that is difficult to quantify with standardized tests. Careful analysis of connected speech can provide valuable information about a patient's language capacities. To date, this type of analysis has been limited by its time-consuming nature. In this study, we present a method for evaluating and classifying connected speech in primary progressive aphasia using computational techniques. Syntactic and semantic features were automatically extracted from transcriptions of narrative speech for three groups: semantic dementia (SD), progressive nonfluent aphasia (PNFA), and healthy controls. Features that varied significantly between the groups were used to train machine learning classifiers, which were then tested on held-out data. We achieved accuracies well above baseline on the three binary classification tasks. An analysis of the influential features showed that in contrast with controls, both patient groups tended to use words which were higher in frequency (especially nouns for SD, and verbs for PNFA). The SD patients also tended to use words (especially nouns) that were higher in familiarity, and they produced fewer nouns, but more demonstratives and adverbs, than controls. The speech of the PNFA group tended to be slower and incorporate shorter words than controls. The patient groups were distinguished from each other by the SD patients' relatively increased use of words which are high in frequency and/or familiarity.
Key findings
- Features that varied significantly between the groups were used to train machine learning classifiers, which were then tested on held-out data.
- An analysis of the influential features showed that in contrast with controls, both patient groups tended to use words which were higher in frequency (especially nouns for SD, and verbs for PNFA).
Why it matters
This study describes a computational method that classified connected speech from patients with semantic dementia and progressive nonfluent aphasia with accuracy above baseline. It is a diagnostic and classification tool, not a treatment, cure, or prevention for Alzheimer's disease.
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Study details
- Evidence strengthLow
How this study scored 36/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 23 of the 64 points we could judge it on, which is 36 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Cortex; a journal devoted to the study of the nervous system and behavior) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2014 — within 20 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (OpenAlex dates this DOI to 2012, the record says 2014; OpenAlex values not used) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | 2 / 6 | Cited by 6 other studies in this library |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 23332818) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 23 / 64 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 23 of the 64 points we could judge it on is 36 out of 100. |
| Total | 36 / 100 | — |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Fraser, K. C., Meltzer, J. A., Graham, N. L., Leonard, C., Hirst, G., Black, S. E., et al. (2014). Automated classification of primary progressive aphasia subtypes from narrative speech transcripts. Cortex; a journal devoted to the study of the nervous system and behavior. https://doi.org/10.1016/j.cortex.2012.12.006
Vancouver
Fraser KC, Meltzer JA, Graham NL, Leonard C, Hirst G, Black SE, et al. Automated classification of primary progressive aphasia subtypes from narrative speech transcripts. Cortex; a journal devoted to the study of the nervous system and behavior. 2014. doi:10.1016/j.cortex.2012.12.006. PMID: 23332818.
BibTeX
@article{fraser2014-23332818,
author = {Fraser, K. C. and Meltzer, J. A. and Graham, N. L. and Leonard, C. and Hirst, G. and Black, S. E. and Rochon, E.},
title = {{Automated classification of primary progressive aphasia subtypes from narrative speech transcripts}},
journal = {Cortex; a journal devoted to the study of the nervous system and behavior},
year = {2014},
doi = {10.1016/j.cortex.2012.12.006},
pmid = {23332818},
url = {https://doi.org/10.1016/j.cortex.2012.12.006}
}
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