What is Model drift?
Model drift, the model's performance deteriorating over time.
In terms of data and intelligence
In the context of artificial intelligence, model drift is evaluated alongside model quality, data quality, compliance with KVKK, and principles of explainability.
How does it work?
In addition to model performance, data quality, explainability, and regulatory compliance are also part of success.
Why is it important?
When addressed correctly, model drift helps teams work with fewer errors and faster; it also allows management to make decisions based on more solid data.
For more in-depth information, you can visit the AI-Powered Hospital Management page, and for related concepts, check the Digital Dictionary page.
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What is model drift?
The model's performance deteriorating over time.
How is model drift used in AI-supported processes?
Model drift plays a role in transforming clinical and operational data into insights; it does not make decisions but supports the decisions of relevant teams.
Who is concerned with model drift?
Model drift is of interest to teams working in the field of Artificial Intelligence, primarily data/analytics teams and managers seeking decision support.