↓ Skip to main content

Classification of Alzheimer’s Disease Leveraging Multi-task Machine Learning Analysis of Speech and Eye-Movement Data

Overview of attention for article published in Frontiers in Human Neuroscience, September 2021
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

news
1 news outlet
twitter
3 X users

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
43 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Classification of Alzheimer’s Disease Leveraging Multi-task Machine Learning Analysis of Speech and Eye-Movement Data
Published in
Frontiers in Human Neuroscience, September 2021
DOI 10.3389/fnhum.2021.716670
Pubmed ID
Authors

Hyeju Jang, Thomas Soroski, Matteo Rizzo, Oswald Barral, Anuj Harisinghani, Sally Newton-Mason, Saffrin Granby, Thiago Monnerat Stutz da Cunha Vasco, Caitlin Lewis, Pavan Tutt, Giuseppe Carenini, Cristina Conati, Thalia S. Field

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 9%
Researcher 3 7%
Student > Bachelor 3 7%
Lecturer > Senior Lecturer 2 5%
Student > Doctoral Student 2 5%
Other 3 7%
Unknown 26 60%
Readers by discipline Count As %
Computer Science 3 7%
Medicine and Dentistry 3 7%
Psychology 3 7%
Biochemistry, Genetics and Molecular Biology 2 5%
Social Sciences 2 5%
Other 3 7%
Unknown 27 63%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 October 2021.
All research outputs
#3,611,457
of 26,456,908 outputs
Outputs from Frontiers in Human Neuroscience
#1,664
of 7,837 outputs
Outputs of similar age
#77,377
of 440,953 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#24
of 187 outputs
Altmetric has tracked 26,456,908 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,837 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.2. This one has done well, scoring higher than 78% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 440,953 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.