Open AccessReply: Predicting sperm extraction in non-obstructive azoospermia patients: a machine-learning perspective
Author(s) -
Atif Zeadna,
N Khateeb,
Lior Rokach,
Yotam Lior,
Iris HarVardi,
Avi Harlev,
Mahmoud Huleihel,
Eitan Lunenfeld,
Eliahu Levitas
Publication year - 2020
Publication title -
human reproduction
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 2.446
H-Index - 226
eISSN - 1460-2350
pISSN - 0268-1161
DOI - 10.1093/humrep/deaa259
Subject(s) - perspective (graphical) , testicular sperm extraction , obstructive azoospermia , azoospermia , sperm , andrology , gynecology , medicine , computer science , biology , artificial intelligence , infertility , pregnancy , genetics
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