Based on the given feature "ant_im" and the task of determining if the patient has chronic heart failure, we need to analyze the relationship between this feature and the target variable.

To do this, we can look at how different values of "ant_im" are associated with the presence or absence of chronic heart failure. By examining the data, we can then identify the possible values of "ant_im" that correspond to each target class.

Here is the analysis result and the dictionary with the specific details:

```json
{
	"no": ["there is no infarct in this location", "QRS has no changes"], 
	"yes": ["QRS is like QS-complex", "QRS is like QR-complex"]
}
```

Explanation:
- If the value of "ant_im" is "there is no infarct in this location" or "QRS has no changes", the patient is classified as having no chronic heart failure.
- If the value of "ant_im" is "QRS is like QS-complex" or "QRS is like QR-complex", the patient is classified as having chronic heart failure.

Other possible values of "ant_im" are not included in the dictionary as they are not strongly indicative or their relationship with chronic heart failure is uncertain. However, the list for each target class is not empty, indicating that at least some values of "ant_im" are associated with the corresponding class.