Prediction of future gastric cancer risk using a machine learning algorithm and comprehensive medical check-up data: A case-control study

A comprehensive screening method using machine learning and many factors (biological characteristics, Helicobacter pylori infection status, endoscopic findings and blood test results), accumulated daily as data in hospitals, could improve the accuracy of screening to classify patients at high or low...

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Detalles Bibliográficos
Autores principales: Taninaga, Junichi, Nishiyama, Yu, Fujibayashi, Kazutoshi, Gunji, Toshiaki, Sasabe, Noriko, Iijima, Kimiko, Naito, Toshio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6712020/
https://www.ncbi.nlm.nih.gov/pubmed/31455831
http://dx.doi.org/10.1038/s41598-019-48769-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6712020/
https://www.ncbi.nlm.nih.gov/pubmed/31455831
http://dx.doi.org/10.1038/s41598-019-48769-y

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