The application of machine learning for predicting recurrence in patients with early-stage endometrial cancer: a pilot study

• Huvudupphovsmän: Munetoshi Akazawa (Författare, medförfattare), Kazunori Hashimoto (Författare, medförfattare), Katsuhiko Noda (Författare, medförfattare), Kaname Yoshida (Författare, medförfattare)
• Materialtyp: Bok
• Publicerad: Korean Society of Obstetrics and Gynecology, 2021-05-01T00:00:00Z.
• Ämnen: article
• Länkar: Connect to this object online.

Objective Most women with early stage endometrial cancer have a favorable prognosis. However, there is a subset of patients who develop recurrence. In addition to the pathological stage, clinical and therapeutic factors affect the probability of recurrence. Machine learning is a subtype of artificia...