Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Qianqing Ma"'
Publikováno v:
Renal Failure, Vol 45, Iss 2 (2023)
This study aimed to develop and validate a combined nomogram model based on superb microvascular imaging (SMI)-based deep learning (DL), radiomics characteristics, and clinical factors for noninvasive differentiation between immunoglobulin A nephropa
Externí odkaz:
https://doaj.org/article/f9e334b68d3e4c92a25af28c48900e26
Publikováno v:
Frontiers in Medicine, Vol 9 (2022)
Background and aimsThe present study aimed to analyze the effects of factors on cystocele and the Green classification.Materials and methodsWe conducted a cross-sectional study on 357 primiparous women examined at our hospital from January 2019 to Ma
Externí odkaz:
https://doaj.org/article/cafc99498d114972896d709a19a75ee1
Autor:
Qianqing Ma, Chunyun Shen, Yankun Gao, Yayang Duan, Wanyan Li, Gensheng Lu, Xiachuan Qin, Chaoxue Zhang, Junli Wang
Publikováno v:
Breast Cancer: Targets and Therapy. 15:381-390
Qianqing Ma,1,* Chunyun Shen,2,* Yankun Gao,3,* Yayang Duan,1 Wanyan Li,4 Gensheng Lu,5 Xiachuan Qin,1 Chaoxue Zhang,1 Junli Wang2 1Department of Ultrasound, the First Affiliated Hospital of Anhui Medical University, Hefei, Peopleâs
Publikováno v:
Academic Radiology.
To develop and validate a nomogram for predicting the risk of malignancy of breast imaging reporting and data system (BI-RADS) 4A lesions to reduce unnecessary invasive examinations.From January 2017 to July 2021, 190 cases of 4A lesions included in
Publikováno v:
Academic radiology.
Prediction of microvascular invasion (MVI) status of hepatocellular carcinoma (HCC) holds clinical significance for decision-making regarding the treatment strategy and evaluation of patient prognosis. We developed a deep learning (DL) model based on