Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Shaolei Yan"'
Autor:
Haiyong Peng, Shaolei Yan, Xiaodan Chen, Jiahang Hu, Kaige Chen, Ping Wang, Hongxia Zhang, Xiushi Zhang, Wei Meng
Publikováno v:
Frontiers in Oncology, Vol 12 (2022)
PurposeThis study aimed to assess the diagnostic performance and the added value to radiologists of different levels of a computer-aided diagnosis (CAD) system for the detection of pathological complete response (pCR) after neoadjuvant chemotherapy (
Externí odkaz:
https://doaj.org/article/e7ea75bcbb7e4b2f9199abb8fba500b3
Autor:
Wei Meng, Yunfeng Sun, Haibin Qian, Xiaodan Chen, Qiujie Yu, Nanding Abiyasi, Shaolei Yan, Haiyong Peng, Hongxia Zhang, Xiushi Zhang
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
BackgroundThere is a demand for additional alternative methods that can allow the differentiation of the breast tumor into molecular subtypes precisely and conveniently.PurposeThe present study aimed to determine suitable optimal classifiers and inve
Externí odkaz:
https://doaj.org/article/98edaf691cf54fa0a3cf225eae084865
Autor:
Shaolei Yan, Haiyong Peng, Qiujie Yu, Xiaodan Chen, Yue Liu, Ye Zhu, Kaige Chen, Ping Wang, Yujiao Li, Xiushi Zhang, Wei Meng
Publikováno v:
Future Oncology. 18:991-1001
Background: To determine suitable optimal classifiers and examine the general applicability of computer-aided classification to compare the differences between a computer-aided system and radiologists in predicting pathological complete response (pCR
Autor:
Ping Wang, Kaige Chen, Ying Han, Min Zhao, Nanding Abiyasi, Jiming Shang, Shaolei Yan, Haiyong Peng, Naijian Shang, Wei Meng
Objective Lymphovascular invasion (LVI) is an independent risk factor of gastric cancer (GC) prognosis; however, LVI cannot be determined preoperatively. We explored whether a model based on contrast-enhanced computed tomography (CECT) radiomics feat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::160e4cc1f24552abc99a3e9127ebb08e
https://doi.org/10.21203/rs.3.rs-2107626/v1
https://doi.org/10.21203/rs.3.rs-2107626/v1
Autor:
Haibin Qian, Nanding Abiyasi, Haiyong Peng, Shaolei Yan, Xiu-Shi Zhang, Qiujie Yu, Wei Meng, Xiaodan Chen, Yun-Feng Sun, Hong-Xia Zhang
Publikováno v:
Frontiers in Oncology
Frontiers in Oncology, Vol 11 (2021)
Frontiers in Oncology, Vol 11 (2021)
BackgroundThere is a demand for additional alternative methods that can allow the differentiation of the breast tumor into molecular subtypes precisely and conveniently.PurposeThe present study aimed to determine suitable optimal classifiers and inve
Publikováno v:
Sensors, Vol 23, Iss 19, p 8148 (2023)
The rapid growth in dataset sizes in modern deep learning has significantly increased data storage costs. Furthermore, the training and time costs for deep neural networks are generally proportional to the dataset size. Therefore, reducing the datase
Externí odkaz:
https://doaj.org/article/f08598a260dc417686e8b8738b63deae
Publikováno v:
Healthcare, Vol 8, Iss 3, p 270 (2020)
In the face of increasingly growing health demands and the impact of various public health emergencies, it is of great significance to study the regional differences in the allocation efficiency of the rural public health resources and its improvemen
Externí odkaz:
https://doaj.org/article/9755faa192aa49f2b2e962490cdd87f1