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A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology
28
Zitationen
4
Autoren
2021
Jahr
Abstract
ES utility offers an effective ML potential and their applications in research have demonstrated a valid model for multi-variate analysis. The complexity of their development can challenge their uptake in urological clinics whilst the limitation of the statistical tools in this domain has created a gap for further research studies. Integration of computer scientists in academic units has promoted the use of ES in clinical urological research.
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