Based on prior knowledge, we can analyze the relationship between the feature "ASP_S_n" and the task of determining whether the patient shows chronic heart failure.

Since "ASP_S_n" represents the use of acetylsalicylic acid in the Intensive Care Unit (ICU), we can hypothesize that patients who were given acetylsalicylic acid might have a lower likelihood of experiencing chronic heart failure complications.

To analyze this relationship, we need to examine the distribution of the "ASP_S_n" values for each class of the target variable (chronic heart failure).

Possible scenarios:

1. Chronic Heart Failure (yes):
- ASP_S_n: ['yes', 'no']

2. Chronic Heart Failure (no):
- ASP_S_n: ['yes', 'no']

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

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

This dictionary states that for patients with chronic heart failure (yes) and those without chronic heart failure (no), both categories ('yes' and 'no') of the feature "ASP_S_n" appeared.