RADI-22. CHARACTERIZING CLINICAL SURVIVAL PATTERNS USING MACHINE LEARNING: AN ANALYSIS OF BRAIN METASTASIS PATIENTS TREATED WITH STEREOTACTIC RADIOSURGERY

INTRODUCTION: Increased sophistication in machine-learning algorithms and artificial intelligence have begun to unveil patterns that would be otherwise unappreciated in clinical medicine. Here we applied one such algorithm, Iterative Factorial Analysis of Mixed Data (IFAMD), to better understanding...

Descripción completa

Detalles Bibliográficos
Autores principales: Alattar, Ali, Joshi, Rushikesh, HIrshman, Brian, Carroll, Kate, Nagano, Osamu, Aiyama, Hitoshi, Serizawa, Toru, Yamamoto, Masaaki, Chen, Clark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Abstracts
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7213108/
http://dx.doi.org/10.1093/noajnl/vdz014.114

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7213108/
http://dx.doi.org/10.1093/noajnl/vdz014.114

Ejemplares similares