A novel indirect method for deriving reference intervals through iterative data cleaning guided by self-organizing maps of multi-test patterns (SOM-clean)
Key Points
This method enhances the accuracy of reference intervals derived from laboratory data, improving clinical decision-making.
Using novel self-organizing maps, reference intervals were estimated with greater precision than traditional methods.
SOM-clean utilizes a multivariate approach to data cleaning, ensuring robust results across various tests.
The implications support better understanding and implementation of reference intervals in clinical settings.
Abstract
SOM-clean represents a practical and robust parametric tool for estimating RIs indirectly from routine laboratory data employing a novel multivariate-based data cleaning scheme.
A novel indirect method for deriving reference intervals through iterative data cleaning guided by self-organizing maps of multi-test patterns (SOM-clean) | Synapse