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Artificial Intelligence-based Interpretation of Race and Sex Disparities among U.S. Internal Medicine Faculty: A Comparative Analysis.

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Title: Artificial Intelligence-based Interpretation of Race and Sex Disparities among U.S. Internal Medicine Faculty: A Comparative Analysis.
Authors: Quon, Stephanie1 (AUTHOR) stephaniesfquon@gmail.com, Zheng, Katherine1 (AUTHOR)
Source: APIK Journal of Internal Medicine. Jul-Sep2026, Vol. 14 Issue 3, p200-210. 11p.
Database: Academic Search Ultimate
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  Data: Artificial Intelligence-based Interpretation of Race and Sex Disparities among U.S. Internal Medicine Faculty: A Comparative Analysis.
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  Data: <searchLink fieldCode="AR" term="%22Quon%2C+Stephanie%22">Quon, Stephanie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> stephaniesfquon@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Zheng%2C+Katherine%22">Zheng, Katherine</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22APIK+Journal+of+Internal+Medicine%22">APIK Journal of Internal Medicine</searchLink>. Jul-Sep2026, Vol. 14 Issue 3, p200-210. 11p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=194976981
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        Value: 10.4103/ajim.ajim_12_26
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 200
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      – TitleFull: Artificial Intelligence-based Interpretation of Race and Sex Disparities among U.S. Internal Medicine Faculty: A Comparative Analysis.
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              Text: Jul-Sep2026
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              Y: 2026
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