Based on the provided feature description and task, we need to analyze how the feature "lat_im" relates to the presence of chronic heart failure in patients with myocardial infarction complications.

Since the feature "lat_im" represents the presence of a lateral myocardial infarction, which is an ECG change in specific leads, we can infer that the presence or absence of chronic heart failure may be related to the type of ECG changes observed in those leads.

To analyze the relationship, we need more information about the specific ECG changes associated with chronic heart failure. Without that information, it is difficult to make a precise prediction regarding whether a specific "lat_im" value indicates chronic heart failure.

Therefore, the analysis suggests that the "lat_im" feature alone may not provide a clear indication of chronic heart failure. Further information or additional features might be needed to make a more accurate prediction.

Based on this analysis, here is the dictionary representing the possible values of the "lat_im" feature for each target class:

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

Note that in this case, all the possible values of "lat_im" are included in both target classes, as we don't have enough information to exclude any specific value based on the task.