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[Artificial intelligence: to a better predictive strategy for testicular sperm extraction outcome in azoospermia]. / Intelligence artificielle : vers une meilleure stratégie de prédiction du résultat de la biopsie testiculaire dans un contexte d'azoospermie.
Bachelot, Guillaume; Ly, Anna; Rivet-Danon, Diane; Sermondade, Nathalie; Frydman, Valentine; Lamazière, Antonin; Haj Hamid, Rahaf; Levy, Rachel; Dupont, Charlotte.
Affiliation
  • Bachelot G; Sorbonne Université, Faculté de Médecine, Saint Antoine Research Center, INSERM UMR 938, 27 rue Chaligny, Paris, France, Service de Biologie de la Reproduction-CECOS, Hôpital Tenon, AP-HP, Sorbonne Université, 75020 Paris, France.
  • Ly A; Service de Biologie de la Reproduction-CECOS, Hôpital Tenon, AP-HP, Sorbonne Université, 75020 Paris, France.
  • Rivet-Danon D; Service de Biologie de la Reproduction-CECOS, Hôpital Tenon, AP-HP, Sorbonne Université, 75020 Paris, France.
  • Sermondade N; Sorbonne Université, Faculté de Médecine, Saint Antoine Research Center, INSERM UMR 938, 27 rue Chaligny, Paris, France, Service de Biologie de la Reproduction-CECOS, Hôpital Tenon, AP-HP, Sorbonne Université, 75020 Paris, France.
  • Frydman V; Service d'Urologie, Hôpital Tenon, AP-HP, Sorbonne Université, 75020 Paris, France.
  • Lamazière A; Sorbonne Université, Faculté de Médecine, Saint Antoine Research Center, INSERM UMR 938, 27 rue Chaligny, Paris, France, Département de Métabolomique Clinique, Hôpital Saint Antoine, AP-HP, Sorbonne Université, 75012 Paris, France.
  • Haj Hamid R; Service de Biologie de la Reproduction-CECOS, Hôpital Tenon, AP-HP, Sorbonne Université, 75020 Paris, France.
  • Levy R; Sorbonne Université, Faculté de Médecine, Saint Antoine Research Center, INSERM UMR 938, 27 rue Chaligny, Paris, France, Service de Biologie de la Reproduction-CECOS, Hôpital Tenon, AP-HP, Sorbonne Université, 75020 Paris, France.
  • Dupont C; Sorbonne Université, Faculté de Médecine, Saint Antoine Research Center, INSERM UMR 938, 27 rue Chaligny, Paris, France, Service de Biologie de la Reproduction-CECOS, Hôpital Tenon, AP-HP, Sorbonne Université, 75020 Paris, France.
Ann Biol Clin (Paris) ; 82(2): 139-149, 2024 06 05.
Article de Fr | MEDLINE | ID: mdl-38702888
ABSTRACT
Azoospermia, defined as the absence of sperm in the semen, is found in 10-15 % of infertile patients. Two-thirds of these cases are caused by impaired spermatogenesis, known as non-obstructive azoospermia (NOA). In this context, surgical sperm extraction using testicular sperm extraction (TESE) is the best option and can be offered to patients as part of fertility preservation, or to benefit from in vitro fertilization. The aim of the preoperative assessment is to identify the cause of NOA and evaluate the status of spermatogenesis. Its capacity to predict TESE success remains limited. As a result, no objective and reliable criteria are currently available to guide professionals on the chances of success and enable them to correctly assess the benefit-risk balance of this procedure. Artificial intelligence (AI), a field of research that has been rapidly expanding in recent years, has the potential to revolutionize medicine by making it more predictive and personalized. The aim of this review is to introduce AI and its key concepts, and then to examine the current state of research into predicting the success of TESE.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Intelligence artificielle / Azoospermie / Prélèvement de sperme Limites: Humans / Male Langue: Fr Journal: Ann Biol Clin (Paris) Année: 2024 Type de document: Article Pays d'affiliation: France

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Intelligence artificielle / Azoospermie / Prélèvement de sperme Limites: Humans / Male Langue: Fr Journal: Ann Biol Clin (Paris) Année: 2024 Type de document: Article Pays d'affiliation: France