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Machine learning based prediction models in male reproductive health: Development of a proof‐of‐concept model for Klinefelter Syndrome in azoospermic patients
Author(s) -
Krenz Henrike,
Sansone Andrea,
Fujarski Michael,
Krallmann Claudia,
Zitzmann Michael,
Dugas Martin,
Kliesch Sabine,
Varghese Julian,
Tüttelmann Frank,
Gromoll Jörg
Publication year - 2022
Publication title -
andrology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.947
H-Index - 43
eISSN - 2047-2927
pISSN - 2047-2919
DOI - 10.1111/andr.13141
Subject(s) - klinefelter syndrome , machine learning , gynecomastia , medicine , azoospermia , artificial intelligence , luteinizing hormone , gynecology , computer science , infertility , hormone , biology , pregnancy , genetics
Due to the highly variable clinical phenotype, Klinefelter Syndrome is underdiagnosed.
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