A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology

BACKGROUND: Testing a hypothesis for ‘factors-outcome effect’ is a common quest, but standard statistical regression analysis tools are rendered ineffective by data contaminated with too many noisy variables. Expert Systems (ES) can provide an alternative methodology in analysing data to identify va...

Descripción completa

Detalles Bibliográficos
Autores principales: Salem, Hesham, Soria, Daniele, Lund, Jonathan N., Awwad, Amir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299670/
https://www.ncbi.nlm.nih.gov/pubmed/34294092
http://dx.doi.org/10.1186/s12911-021-01585-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299670/
https://www.ncbi.nlm.nih.gov/pubmed/34294092
http://dx.doi.org/10.1186/s12911-021-01585-9

Ejemplares similares