diff --git a/tests/test_stainnorm.py b/tests/test_stainnorm.py
index 5d95faf2b..59d3045be 100644
--- a/tests/test_stainnorm.py
+++ b/tests/test_stainnorm.py
@@ -148,7 +148,9 @@ def test_macenko_normalize(source_image: Path, norm_macenko: Path) -> None:
     assert np.mean(np.absolute(macenko_img / 255.0 - transform / 255.0)) < 1e-2
 
 
-def test_vahadane_normalize(source_image: Path, norm_vahadane: Path) -> None:
+def test_vahadane_normalize(
+    source_image: Path, norm_vahadane: Path, caplog: pytest.LogCaptureFixture
+) -> None:
     """Test for stain normalization with stain matrix from Vahadane et al."""
     source_img = imread(Path(source_image))
     target_img = stain_norm_target()
@@ -158,7 +160,7 @@ def test_vahadane_normalize(source_image: Path, norm_vahadane: Path) -> None:
     norm = get_normalizer("vahadane")
     norm.fit(target_img)  # get stain information of target image
     transform = norm.transform(source_img)  # transform source image
-
+    assert "Vahadane stain extraction/normalization algorithms" in caplog.text
     assert np.shape(transform) == np.shape(source_img)
     assert np.mean(np.absolute(vahadane_img / 255.0 - transform / 255.0)) < 1e-1
 
diff --git a/tiatoolbox/tools/stainextract.py b/tiatoolbox/tools/stainextract.py
index cb2972ae2..f9041b923 100644
--- a/tiatoolbox/tools/stainextract.py
+++ b/tiatoolbox/tools/stainextract.py
@@ -5,6 +5,7 @@
 import numpy as np
 from sklearn.decomposition import DictionaryLearning
 
+from tiatoolbox import logger
 from tiatoolbox.utils.misc import get_luminosity_tissue_mask
 from tiatoolbox.utils.transforms import rgb2od
 
@@ -238,6 +239,13 @@ class VahadaneExtractor:
     This class contains code inspired by StainTools
     [https://github.com/Peter554/StainTools] written by Peter Byfield.
 
+    .. warning::
+        Vahadane stain extraction/normalization algorithms are unstable
+        after the update to `dictionary learning` algorithm in
+        scikit-learn > v0.23.0 (see issue #382). Please be advised and
+        consider using other stain extraction (normalization) algorithms
+        or toolboxes, such as https://github.com/CielAl/torch-staintools
+
     Args:
         luminosity_threshold (float):
             Threshold used for tissue area selection.
@@ -259,6 +267,14 @@ def __init__(
         regularizer: float = 0.1,
     ) -> None:
         """Initialize :class:`VahadaneExtractor`."""
+        # Issue a warning about the algorithm's stability
+        logger.warning(
+            "Vahadane stain extraction/normalization algorithms are unstable "
+            "after the update to `dictionary learning` algorithm in "
+            "scikit-learn > v0.23.0 (see issue #382). Please be advised and "
+            "consider using other stain extraction (normalization) algorithms.",
+            stacklevel=2,
+        )
         self.__luminosity_threshold = luminosity_threshold
         self.__regularizer = regularizer
 
@@ -267,7 +283,7 @@ def get_stain_matrix(self: VahadaneExtractor, img: np.ndarray) -> np.ndarray:
 
         Args:
             img (:class:`numpy.ndarray`):
-                Input image used for stain matrix estimation
+                Input image used for stain matrix estimation.
 
         Returns:
             :class:`numpy.ndarray`: