IFCC webinar: MACHINE LEARNING IN LABORATORY MEDICINE – RECOMMENDATION OF THE IFCC WORKING GROUP - PART 1
I spoke at an IFCC live webinar to explain our white paper on machine learing. Here are my slides.
Abstract:
During the webinar, my focus has been on how to evaluate machine learing models as a specialist in Laboratory Medicine. Interpretability methods are key to compare domain knowledge with the model’s inner workings. Standardization of analyses with tracability to reference methods is required for greater tranferability of machine learning models.
References:
- Master, SR. et al.; ClinChem (2023); https://doi.org/10.1093/clinchem/hvad055
Slides
How to evaluate machine learning models in Laboratory Medicine?