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Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review.

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Title: Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review.
Authors: Hansun, Seng1,2, s.hansun@unsw.edu.au, Argha, Ahmadreza3,4,5, Bakhshayeshi, Ivan3,6, Wicaksana, Arya7, Alinejad-Rokny, Hamid4,5,6, Fox, Greg J8, Liaw, Siaw-Teng9, Celler, Branko G10, Marks, Guy B1,2,11
Source: Journal of Medical Internet Research; 2025, Vol. 27, p1-23, 23p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 190700834
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Medical+Internet+Research%22">Journal of Medical Internet Research</searchLink>; 2025, Vol. 27, p1-23, 23p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=190700834
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        Value: 10.2196/69068
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        Text: English
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      – TitleFull: Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review.
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              Text: 2025
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