Machine learning in the clinical microbiology laboratory: has the time come for routine practice?
120 Citations•2020•
Nathan Peiffer‐Smadja, Sarah Dellière, Christophe Rodriguez
The evaluation and implementation processes represent the main gap of existing ML systems, requiring a focus on their interpretability and potential integration into real-world settings.
Abstract
In clinical microbiology, ML has been used with various data sources and diverse practical applications. The evaluation and implementation processes represent the main gap in existing ML systems, requiring a focus on their interpretability and potential integration into real-world settings.