Application of Machine Learning in the Diagnosis of Early Gastric Cancer Using the Kyoto Classification Score and Clinical Features Collected from Medical Consultations
The early detection accuracy of early gastric cancer (EGC) determines the choice of the optimal treatment strategy and the related medical expenses. We aimed to develop a simple, affordable, and time-saving diagnostic model using six machine learning (ML) algorithms for the diagnosis of EGC. It is b...
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| Autors principals: | , , , , , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI AG
2024-09-01
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| Col·lecció: | Bioengineering |
| Matèries: | |
| Accés en línia: | https://www.mdpi.com/2306-5354/11/10/973 |
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