Based on my prior knowledge, the use of beta-blockers in the ICU can have an impact on the occurrence of chronic heart failure. Beta-blockers are commonly used in patients with heart failure as they can improve symptoms and reduce the risk of complications.

To analyze the relationship between the feature "B_BLOK_S_n" and the presence of chronic heart failure, we can examine the distribution of the feature values for each target class (yes or no). 

Here's an analysis of the relationship between the feature and the task:

- For the target class "no" (indicating no chronic heart failure), it is expected that the use of beta-blockers in the ICU would be less common. Patients without chronic heart failure might not require beta-blockers as a regular treatment.

- For the target class "yes" (indicating the presence of chronic heart failure), it is more likely that the use of beta-blockers in the ICU would be more frequent. Beta-blockers are a standard treatment for heart failure, and their use is recommended in patients with chronic heart failure.

Based on this analysis, we can create a dictionary with the following format:

```json
{
	"no": ["no"],  
	"yes": ["yes"]
}
```

Since the feature "B_BLOK_S_n" is a categorical variable with only two categories ('no' and 'yes'), we can simply map these categories to the corresponding target class. Note that there might be other possible values for this feature, but since the task is specifically about chronic heart failure, we only include the 'no' and 'yes' categories in the dictionary.

Please let me know if you need any further clarification.