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Artificial intelligence approaches for tinnitus diagnosis: leveraging high-frequency audiometry data for enhanced clinical predictions

Overview of attention for article published in Frontiers in Artificial Intelligence, May 2024
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Title
Artificial intelligence approaches for tinnitus diagnosis: leveraging high-frequency audiometry data for enhanced clinical predictions
Published in
Frontiers in Artificial Intelligence, May 2024
DOI 10.3389/frai.2024.1381455
Pubmed ID
Authors

Seyed-Ali Sadegh-Zadeh, Alireza Soleimani Mamalo, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Reza Hajizadeh, Amir Sam Roshani, Shima Habibzadeh, Shayan Saadat, Majid Behmanesh, Mozafar Saadat, Sahar Sayyadi Gargari

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 25%
Lecturer 1 25%
Unknown 2 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 25%
Computer Science 1 25%
Unknown 2 50%