Add event-free survival evaluation

evaluate_auc_v2.py

@@ -395,40 +395,7 @@ def _metadata_count_map(dataset: HealthDataset, labels_meta: Optional[pd.DataFra
 
 
 def _get_death_token_ids(dataset: HealthDataset, labels_meta: Optional[pd.DataFrame]) -> List[int]:
-    ids: List[int] = []
-
-    if labels_meta is not None and not labels_meta.empty:
-        meta = labels_meta.copy()
-        if "ICD-10 Chapter (short)" in meta.columns:
-            death_rows = meta[meta["ICD-10 Chapter (short)"].astype(
-                str) == "Death"]
-            code_col = _first_existing_column(
-                death_rows, ["Name", "code", "ICD10", "icd10", "label", "token", "disease_code"])
-            if code_col is not None:
-                for raw in death_rows[code_col].astype(str).tolist():
-                    code = raw.split()[0].strip()
-                    if code in dataset.label_code_to_id:
-                        ids.append(int(dataset.label_code_to_id[code]))
-            elif "index" in death_rows.columns:
-                idx = pd.to_numeric(death_rows["index"], errors="coerce")
-                has_no_event = (
-                    NO_EVENT_IDX in dataset.label_id_to_code
-                    and dataset.label_id_to_code.get(NO_EVENT_IDX) == "<NO_EVENT>"
-                )
-                if has_no_event:
-                    idx = idx.where(idx < NO_EVENT_IDX, idx + 1)
-                ids.extend(int(x) for x in idx.dropna().astype(int).tolist())
-
-    exact_codes = {"death", "<death>", "dth", "deceased", "mortality"}
-    for token, code in dataset.label_id_to_code.items():
-        token = int(token)
-        if token in SPECIAL_TOKENS:
-            continue
-        text = str(code).strip().lower()
-        if text in exact_codes or ("death" in text) or ("mortality" in text):
-            ids.append(token)
-
-    return sorted(set(int(x) for x in ids if int(x) not in SPECIAL_TOKENS))
+    return [int(dataset.vocab_size) - 1]
 
 
 def _build_first_occurrence_maps(