Development and validation of an artificial neural network model for non-invasive gastric cancer screening and diagnosis

Non-invasive and cost-effective diagnosis of gastric cancer is essential to improve outcomes. Aim of the study was to establish a neural network model based on patient demographic data and serum biomarker panels to aid gastric cancer diagnosis. A total of 295 patients hospitalized in Nanjing Drum To...

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Detalles Bibliográficos
Autores principales: Fan, Zeyu, Guo, Yuxin, Gu, Xinrui, Huang, Rongrong, Miao, Wenjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758153/
https://www.ncbi.nlm.nih.gov/pubmed/36526664
http://dx.doi.org/10.1038/s41598-022-26477-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758153/
https://www.ncbi.nlm.nih.gov/pubmed/36526664
http://dx.doi.org/10.1038/s41598-022-26477-4

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