Machine Learning and Radiogenomics: Lessons Learned and Future Directions

Due to the rapid increase in the availability of patient data, there is significant interest in precision medicine that could facilitate the development of a personalized treatment plan for each patient on an individual basis. Radiation oncology is particularly suited for predictive machine learning...

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Detalles Bibliográficos
Autores principales: Kang, John, Rancati, Tiziana, Lee, Sangkyu, Oh, Jung Hun, Kerns, Sarah L., Scott, Jacob G., Schwartz, Russell, Kim, Seyoung, Rosenstein, Barry S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6021505/
https://www.ncbi.nlm.nih.gov/pubmed/29977864
http://dx.doi.org/10.3389/fonc.2018.00228

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6021505/
https://www.ncbi.nlm.nih.gov/pubmed/29977864
http://dx.doi.org/10.3389/fonc.2018.00228

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