The data shown below were collected from the profiles of 112 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Title |
Predicting dementia from spontaneous speech using large language models
|
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Published in |
PLOS Digital Health, December 2022
|
DOI | 10.1371/journal.pdig.0000168 |
Pubmed ID | |
Authors |
Felix Agbavor, Hualou Liang |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 10 | 9% |
United Kingdom | 5 | 4% |
Japan | 3 | 3% |
India | 3 | 3% |
Kenya | 2 | 2% |
France | 2 | 2% |
Spain | 1 | <1% |
Palestine, State of | 1 | <1% |
Malawi | 1 | <1% |
Other | 2 | 2% |
Unknown | 82 | 73% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 98 | 88% |
Scientists | 9 | 8% |
Practitioners (doctors, other healthcare professionals) | 4 | 4% |
Science communicators (journalists, bloggers, editors) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 84 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 12 | 14% |
Unspecified | 6 | 7% |
Student > Ph. D. Student | 4 | 5% |
Professor | 4 | 5% |
Student > Bachelor | 4 | 5% |
Other | 12 | 14% |
Unknown | 42 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 10 | 12% |
Psychology | 7 | 8% |
Unspecified | 6 | 7% |
Engineering | 6 | 7% |
Business, Management and Accounting | 3 | 4% |
Other | 11 | 13% |
Unknown | 41 | 49% |