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Feature-Level Insights into the Progesterone–Estradiol Ratio in Postmenopausal Women Using Explainable Machine Learning.

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Title: Feature-Level Insights into the Progesterone–Estradiol Ratio in Postmenopausal Women Using Explainable Machine Learning.
Authors: Hamidovic, Ajna1 (AUTHOR) ahamidov@uic.edu, Davis, John2 (AUTHOR), Burge, Mark R3 (AUTHOR)
Source: AI. Aug2025, Vol. 6 Issue 8, p187. 19p.
Database: Academic Search Ultimate
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  Data: Feature-Level Insights into the Progesterone–Estradiol Ratio in Postmenopausal Women Using Explainable Machine Learning.
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  Data: <searchLink fieldCode="AR" term="%22Hamidovic%2C+Ajna%22">Hamidovic, Ajna</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ahamidov@uic.edu</i><br /><searchLink fieldCode="AR" term="%22Davis%2C+John%22">Davis, John</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Burge%2C+Mark+R%22">Burge, Mark R</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22AI%22">AI</searchLink>. Aug2025, Vol. 6 Issue 8, p187. 19p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=187613508
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        Value: 10.3390/ai6080187
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        Text: English
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        PageCount: 19
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      – TitleFull: Feature-Level Insights into the Progesterone–Estradiol Ratio in Postmenopausal Women Using Explainable Machine Learning.
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            NameFull: Davis, John
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              Text: Aug2025
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