A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology
Abstract 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 ide...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-07-01
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| Series: | BMC Medical Informatics and Decision Making |
| Online Access: | https://doi.org/10.1186/s12911-021-01585-9 |