Prediction of sperm extraction in non-obstructive azoospermia patients: a machine-learning perspective

Abstract STUDY QUESTION Can a machine-learning-based model trained in clinical and biological variables support the prediction of the presence or absence of sperm in testicular biopsy in non-obstructive azoospermia (NOA) patients? SUMMARY ANSWER Our machine-learning model was able to accurately pred...

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Veröffentlicht in:	Human reproduction (Oxford) 2020-07, Vol.35 (7), p.1505-1514
Hauptverfasser:	Zeadna, A, Khateeb, N, Rokach, L, Lior, Y, Har-Vardi, I, Harlev, A, Huleihel, M, Lunenfeld, E, Levitas, E
Format:	Artikel
Sprache:	eng
Schlagworte:	Azoospermia - therapy Female Humans Machine Learning Male Pregnancy Prospective Studies Retrospective Studies Sperm Retrieval Spermatozoa Testis
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