What are some examples of imbalanced data in healthcare?

What are some examples of imbalanced data in healthcare?

Imbalanced data in healthcare often occurs when one class of data is underrepresented. For example, in disease diagnosis, if 90% of the data is from healthy patients and only 10% from patients with a rare disease, the model may struggle to accurately identify the disease.

Can you give me more specific examples?

Sure! One example is in cancer detection, where there may be many more healthy samples than cancerous ones. Another is in predicting rare diseases, where the number of cases is significantly lower compared to common conditions.

How does this imbalance affect AI models?

Imbalance can lead to biased models that perform well on the majority class but poorly on the minority class, resulting in missed diagnoses or incorrect predictions.

What can be done to address this issue?

Techniques like resampling, using synthetic data, or employing algorithms designed to handle imbalanced datasets can help improve model performance.