Development of a Machine Learning Model to Predict Recurrence of Oral Tongue Squamous Cell Carcinoma

SIMPLE SUMMARY: In this study, we developed a generic framework to analyze the Surveillance, Epidemiology, and End Results (SEER) database to generate reliable machine learning (ML) prediction models for cancer recurrence. As a proof-of-concept, using 130,979 oral tongue squamous cell carcinoma pati...

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Detalles Bibliográficos
Autores principales: Fatapour, Yasaman, Abiri, Arash, Kuan, Edward C., Brody, James P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216090/
https://www.ncbi.nlm.nih.gov/pubmed/37345106
http://dx.doi.org/10.3390/cancers15102769

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216090/
https://www.ncbi.nlm.nih.gov/pubmed/37345106
http://dx.doi.org/10.3390/cancers15102769

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