Deep learning model utilizing fluorescence lifetime imaging microscopy and confidence learning for predicting endometrial cancer risk-Reference-Cited by-同舟云学术

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Deep learning model utilizing fluorescence lifetime imaging microscopy and confidence learning for predicting endometrial cancer risk

Published:2025-02 Issue: Volume:181 Page:111620
ISSN:0030-3992
Container-title:Optics & Laser Technology
language:en
Short-container-title:Optics & Laser Technology

Author:

Yang Yuwei,Wang Bo,Chen Qiushu,Wang Tianyou,Yang Weiping,Jiao Liying,Chen Liwen,Zhou Jiacheng,Hou Duantao,Fei Yiyan,Ma Jiong,Wang Chao^ORCID,Mi Lan^ORCID

Funder

National Key Clinical Specialty Discipline Construction Program of China

Postdoctoral Science Foundation of Shanghai Municipality

National Natural Science Foundation of China

Fudan University

Outstanding Youth Science and Technology Talents Program of Sichuan

Shanghai Key Laboratory of Molecular Imaging

Natural Science Foundation of Shanghai Municipality

Spanish Clinical Research Network

National Aerospace Science Foundation of China

Publisher

Elsevier BV

Reference34 articles.

1. Endometrial cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up;Oaknin;Ann. Oncol.,2022

2. ESGO/ESTRO/ESP guidelines for the management of patients with endometrial carcinoma;Concin;Int. J. Gynecol. Cancer,2021

3. The surgical stress response and anesthesia: a narrative review;Ivascu;J. Clin. Med.,2024

4. Bleeding in the retroperitoneal space under the broad ligament as a result of uterine perforation after dilatation and curettage: Report of a case;Tokuda;J. Obstet. Gynaecol. Res.,2017

5. A meta-analysis of the risk factors of surgical site infection after hysterectomy for endometrial cancer;Yang;Int. Wound J.,2024

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