↓ Skip to main content

Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients

Overview of attention for article published in Journal of Voice, November 2021
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#50 of 2,244)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
4 news outlets
twitter
9 X users

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
41 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
Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients
Published in
Journal of Voice, November 2021
DOI 10.1016/j.jvoice.2021.11.004
Pubmed ID
Authors

Carlo Robotti, Giovanni Costantini, Giovanni Saggio, Valerio Cesarini, Anna Calastri, Eugenia Maiorano, Davide Piloni, Tiziano Perrone, Umberto Sabatini, Virginia Valeria Ferretti, Irene Cassaniti, Fausto Baldanti, Andrea Gravina, Ahmed Sakib, Elena Alessi, Filomena Pietrantonio, Matteo Pascucci, Daniele Casali, Zakarya Zarezadeh, Vincenzo Del Zoppo, Antonio Pisani, Marco Benazzo

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 12%
Unspecified 4 10%
Student > Ph. D. Student 4 10%
Researcher 3 7%
Lecturer 2 5%
Other 8 20%
Unknown 15 37%
Readers by discipline Count As %
Unspecified 4 10%
Engineering 4 10%
Computer Science 4 10%
Medicine and Dentistry 3 7%
Nursing and Health Professions 2 5%
Other 8 20%
Unknown 16 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 42. 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 08 February 2022.
All research outputs
#985,872
of 25,394,764 outputs
Outputs from Journal of Voice
#50
of 2,244 outputs
Outputs of similar age
#23,941
of 514,633 outputs
Outputs of similar age from Journal of Voice
#1
of 60 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,244 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 97% 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 514,633 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.