Based on prior knowledge, we can analyze the relationship between the feature "TIKL_S_n" and the target variable "chronic heart failure".

The feature "TIKL_S_n" represents the use of Ticlid in the ICU. Since Ticlid is a medication used to prevent blood clots, it may be related to the occurrence of myocardial infarction complications, which can lead to chronic heart failure.

To analyze the relationship between "TIKL_S_n" and chronic heart failure, we can examine the distribution of "TIKL_S_n" values for both the "yes" and "no" classes of chronic heart failure.

Let's assume we have the following data:

| TIKL_S_n  | Chronic Heart Failure |
| --------- | --------------------- |
| no        | yes                   |
| yes       | no                    |
| no        | no                    |
| yes       | yes                   |
| no        | yes                   |
| yes       | no                    |
| yes       | yes                   |

Based on this data, we can create the following dictionary:

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

In this case, the value "no" of the feature "TIKL_S_n" is associated with the target class "no" (chronic heart failure), while the value "yes" of the feature "TIKL_S_n" is associated with both the target classes "no" and "yes" (chronic heart failure).

Please note that this analysis is based on the provided data. To make more accurate conclusions, a larger dataset and statistical analysis would be necessary.