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

• Main Authors: Guillaume Bachelot (Author), Ferdinand Dhombres (Author), Nathalie Sermondade (Author), Rahaf Haj Hamid (Author), Isabelle Berthaut (Author), Valentine Frydman (Author), Marie Prades (Author), Kamila Kolanska (Author), Lise Selleret (Author), Emmanuelle Mathieu-D'Argent (Author), Diane Rivet-Danon (Author), Rachel Levy (Author), Antonin Lamazière (Author), Charlotte Dupont (Author)
• Format: Book
• Published: JMIR Publications, 2023-06-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

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 accurately predict the s...