zDoda · zarmeen2 · Apr 7, 2026 · Apr 6, 2026 · Apr 6, 2026 · Apr 6, 2026
diff --git a/docs/api/datasets.rst b/docs/api/datasets.rst
@@ -238,6 +238,7 @@ Available Datasets
     datasets/pyhealth.datasets.BMDHSDataset
     datasets/pyhealth.datasets.COVID19CXRDataset
     datasets/pyhealth.datasets.ChestXray14Dataset
+    datasets/pyhealth.datasets.VQARADDataset
     datasets/pyhealth.datasets.TUABDataset
     datasets/pyhealth.datasets.TUEVDataset
     datasets/pyhealth.datasets.ClinVarDataset

diff --git a/docs/api/datasets/pyhealth.datasets.VQARADDataset.rst b/docs/api/datasets/pyhealth.datasets.VQARADDataset.rst
@@ -0,0 +1,11 @@
+pyhealth.datasets.VQARADDataset
+===================================
+
+The VQA-RAD dataset for medical visual question answering. The dataset loader
+converts the public JSON annotations into a flat metadata CSV that PyHealth can
+ingest, and its default task is :class:`~pyhealth.tasks.MedicalVQATask`.
+
+.. autoclass:: pyhealth.datasets.VQARADDataset
+    :members:
+    :undoc-members:
+    :show-inheritance:
diff --git a/docs/api/models/pyhealth.models.MedFlamingo.rst b/docs/api/models/pyhealth.models.MedFlamingo.rst
@@ -3,21 +3,37 @@ pyhealth.models.MedFlamingo
 
 MedFlamingo: multimodal medical few-shot learner.
 
-The separate callable MedFlamingoLayer (gated cross-attention dense block)
-and the complete MedFlamingo model.
+This reference covers the visual resampler, the gated cross-attention
+building block, and the complete MedFlamingo model used in the VQA-RAD
+integration branch.
 
 **Paper:** Moor et al. "Med-Flamingo: a Multimodal Medical Few-shot Learner" ML4H 2023.
 
 .. note::
 
-   This is a stub implementation. The class structure and signatures are
-   in place, but ``forward()`` and ``generate()`` raise ``NotImplementedError``.
+   ``forward()`` follows the PyHealth training contract for dataset-backed
+   classification-style use, while ``generate()`` provides the multimodal
+   prompting path for direct medical VQA generation.
 
-.. autoclass:: pyhealth.models.MedFlamingoLayer
+PerceiverResampler
+------------------
+
+.. autoclass:: pyhealth.models.medflamingo.PerceiverResampler
     :members:
     :undoc-members:
     :show-inheritance:
 
+MedFlamingoLayer
+----------------
+
+.. autoclass:: pyhealth.models.medflamingo.MedFlamingoLayer
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+MedFlamingo
+-----------
+
 .. autoclass:: pyhealth.models.MedFlamingo
     :members:
     :undoc-members:

diff --git a/docs/api/tasks.rst b/docs/api/tasks.rst
@@ -213,6 +213,7 @@ Available Tasks
     DKA Prediction (MIMIC-IV) <tasks/pyhealth.tasks.dka>
     Drug Recommendation <tasks/pyhealth.tasks.drug_recommendation>
     Length of Stay Prediction <tasks/pyhealth.tasks.length_of_stay_prediction>
+    Medical VQA <tasks/pyhealth.tasks.MedicalVQATask>
     Medical Transcriptions Classification <tasks/pyhealth.tasks.MedicalTranscriptionsClassification>
     Mortality Prediction (Next Visit) <tasks/pyhealth.tasks.mortality_prediction>
     Mortality Prediction (StageNet MIMIC-IV) <tasks/pyhealth.tasks.mortality_prediction_stagenet_mimic4>

diff --git a/docs/api/tasks/pyhealth.tasks.MedicalVQATask.rst b/docs/api/tasks/pyhealth.tasks.MedicalVQATask.rst
@@ -0,0 +1,12 @@
+pyhealth.tasks.MedicalVQATask
+===================================
+
+Medical visual question answering task for paired radiology images and
+questions. This task treats VQA-RAD answers as a multiclass prediction target
+so the resulting ``SampleDataset`` can be trained with the standard PyHealth
+trainer loop.
+
+.. autoclass:: pyhealth.tasks.MedicalVQATask
+    :members:
+    :undoc-members:
+    :show-inheritance: