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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2021
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| Materias: | |
| 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 |