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1 Ergebnisse
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Revolutionizing urogynecology: Machine learning application..:
Rotem, Reut
;
Galvin, Daniel
;
Daykan, Yair
...
European Journal of Obstetrics & Gynecology and Reproductive Biology. 300 (2024) - p. 49-53 , 2024
Link:
https://doi.org/10.1016/j.ejogrb.2024.07.009
RT Journal T1 <Title>Revolutionizing urogynecology: Machine learning application with patient-centric technology: Promise, challenges, and future directions</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.ejogrb.2024.07.009&Exemplar=1&LAN=DE A1 Rotem, Reut A1 Galvin, Daniel A1 Daykan, Yair A1 Mi, Yanlin A1 Tabirca, Sabin A1 O'Reilly, Barry A. PB Elsevier BV YR 2024 SN 0301-2115 JF European Journal of Obstetrics & Gynecology and Reproductive Biology VO 300 SP 49 OP 53 LK http://dx.doi.org/https://doi.org/10.1016/j.ejogrb.2024.07.009 DO https://doi.org/10.1016/j.ejogrb.2024.07.009 SF ELIB - SuUB Bremen
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