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Emerging Pathways to Non-Invasive Diagnosis in Endometriosis: Integrating Machine Learning, Deep Learning and Multi-Omics Biomarkers.

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Title: Emerging Pathways to Non-Invasive Diagnosis in Endometriosis: Integrating Machine Learning, Deep Learning and Multi-Omics Biomarkers.
Authors: Markov, Daniel1,2 (AUTHOR), Gurung, Jasmin2,3 (AUTHOR), Khalid, Usman3 (AUTHOR), Bechev, Kristian1,4 (AUTHOR) kristian_bechev@abv.bg, Aleksiev, Vladimir5,6 (AUTHOR), Markov, Galabin3,6 (AUTHOR), Poryazova, Elena1,2,7 (AUTHOR)
Source: Diagnostics (2075-4418). Jun2026, Vol. 16 Issue 12, p1823. 19p.
Database: Academic Search Ultimate
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  Data: Emerging Pathways to Non-Invasive Diagnosis in Endometriosis: Integrating Machine Learning, Deep Learning and Multi-Omics Biomarkers.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=194906738
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.3390/diagnostics16121823
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      – Code: eng
        Text: English
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        StartPage: 1823
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      – TitleFull: Emerging Pathways to Non-Invasive Diagnosis in Endometriosis: Integrating Machine Learning, Deep Learning and Multi-Omics Biomarkers.
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            NameFull: Markov, Daniel
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            NameFull: Gurung, Jasmin
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            NameFull: Khalid, Usman
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            NameFull: Aleksiev, Vladimir
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            NameFull: Markov, Galabin
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            – D: 15
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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