A Machine Learning Approach for the Prediction of Testicular Sperm Extraction in Nonobstructive Azoospermia: Algorithm Development and Validation Study

A Machine Learning Approach for the Prediction of Testicular Sperm Extraction in Nonobstructive Azoospermia: Algorithm Development and Validation Study

BackgroundTesticular sperm extraction (TESE) is an essential therapeutic tool for the management of male infertility. However, it is an invasive procedure with a success rate up to 50%. To date, no model based on clinical and laboratory parameters is sufficiently powerful to...

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Bibliographic Details
Main Authors: Guillaume Bachelot, Ferdinand Dhombres, Nathalie Sermondade, Rahaf Haj Hamid, Isabelle Berthaut, Valentine Frydman, Marie Prades, Kamila Kolanska, Lise Selleret, Emmanuelle Mathieu-D’Argent, Diane Rivet-Danon, Rachel Levy, Antonin Lamazière, Charlotte Dupont
Format: Article
Language:English
Published: JMIR Publications 2023-06-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2023/1/e44047

Internet

https://www.jmir.org/2023/1/e44047

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