Based on prior knowledge, the ECG rhythm at the time of admission to the hospital (feature: ritm_ecg_p_01) is related to the myocardial infarction complications data and can provide insights into the presence of chronic heart failure.

To analyze the relationship between the feature and the task, we need to determine the possible values of ritm_ecg_p_01 for each target class (yes and no). Let's examine the data:

| ritm_ecg_p_01 | Chronic Heart Failure |
|---------------|-----------------------|
|     yes       |          yes          |
|     yes       |           no          |
|     no        |           no          |
|     no        |          yes          |
|     yes       |          yes          |
|     no        |           no          |

From the given data, we can see that when the target class is "no," the feature value for ritm_ecg_p_01 can be both "yes" and "no." On the other hand, when the target class is "yes," the only observed feature value for ritm_ecg_p_01 is "yes."

Based on this analysis, we can create the dictionary:

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

This dictionary captures the possible feature values of ritm_ecg_p_01 for each target class of chronic heart failure.