Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Xinglin Yi"'
Prediction of lung papillary adenocarcinoma-specific survival using ensemble machine learning models
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-8 (2023)
Abstract Accurate prognostic prediction is crucial for treatment decision-making in lung papillary adenocarcinoma (LPADC). The aim of this study was to predict cancer-specific survival in LPADC using ensemble machine learning and classical Cox regres
Externí odkaz:
https://doaj.org/article/5961d9816431499698e8a07e573355e1
Publikováno v:
The Clinical Respiratory Journal, Vol 18, Iss 1, Pp n/a-n/a (2024)
Abstract Introduction This study was to investigate the diagnostic value of percutaneous closed pleural brushing (CPBR) followed by cell block technique for malignant pleural effusion (MPE) and the predictive efficacy of pleural fluid carcinoembryoni
Externí odkaz:
https://doaj.org/article/85c0028f3c1f4699ae6c13d0ed32b14f
Publikováno v:
Cancer Medicine, Vol 13, Iss 1, Pp n/a-n/a (2024)
Abstract Purpose Our study aims to delineate the epidemiological distribution of pulmonary carcinoids, including atypical carcinoid (AC) and typical carcinoid (TC), identify independent prognostic factors, develop an integrative nomogram and examine
Externí odkaz:
https://doaj.org/article/e370fc2181c944aba40f825be56a36a3
Autor:
Xinglin Yi, Yi He, Yu Zhang, Qiuyue Luo, Caixia Deng, Guihua Tang, Jiongye Zhang, Xiangdong Zhou, Hu Luo
Publikováno v:
Frontiers in Public Health, Vol 11 (2023)
BackgroundSilicosis, a severe lung disease caused by inhaling silica dust, predominantly affects workers in industries such as mining and construction, leading to a significant global public health challenge. The purpose of this study is to analyze t
Externí odkaz:
https://doaj.org/article/10c861bcf35445be85dd18d0e8ec4933
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
BackgroundThis study aimed to develop diagnostic and prognostic models for patients with pulmonary sarcomatoid carcinoma (PSC) and distant metastasis (DM).MethodsPatients from the Surveillance, Epidemiology, and End Results (SEER) database were divid
Externí odkaz:
https://doaj.org/article/a48319afc7bc456f89641cbfcd4dcca2
Autor:
Yuhan Zhang, Xinglin Yi, Zhe Tang, Pan Xie, Na Yin, Qiumiao Deng, Lin Zhu, Hu Luo, Kanfu Peng
Publikováno v:
Frontiers in Public Health, Vol 11 (2023)
BackgroundLymph node (LN) metastasis is strongly associated with distant metastasis of renal cell carcinoma (RCC) and indicates an adverse prognosis. Accurate LN-status prediction is essential for individualized treatment of patients with RCC and to
Externí odkaz:
https://doaj.org/article/fcd6892c7e3f4888aa6691d7e75ad0e2
Publikováno v:
International Journal of Clinical Practice, Vol 2023 (2023)
The accuracy of indices widely used to evaluate lung metastasis (LM) in patients with kidney cancer (KC) is insufficient. Therefore, we aimed at developing a model to estimate the risk of developing LM in KC based on a large population size and machi
Externí odkaz:
https://doaj.org/article/ab633ecbf989468e960f7e1ba0ca72b3
Publikováno v:
Advanced Science Letters. 19:1927-1930
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0578e2c2da98a93202488ee33129bbef
https://doi.org/10.1166/asl.2013.4578
https://doi.org/10.1166/asl.2013.4578