researcher2026/OpenMedReason

This data is the Open-PMC derived data part that we discuss in the paper

Medical VQA with Reasoning Traces (Anonymous)

A multiple-choice medical visual question answering benchmark with chain-of-thought reasoning traces. Each example consists of a medical image (radiology, pathology, clinical photograph, etc.), a multiple-choice question with labeled options, a reasoning trace, and the correct answer letter.

This dataset is released anonymously in support of a peer-reviewed submission.

Columns

Perception / Medical knowledge / Rationale are evaluation aids: each is a JSON-encoded list of {topic, claim, presence_question, correctness_question, source_quote, importance} items derived from the reference reasoning trace. They are populated for the test split only and held as "[]" strings on the train split for schema parity (so the dataset viewer works on both splits).

Loading

from datasets import load_dataset
import json

ds = load_dataset("researcher2026/OpenMedReason")
print(ds)
print(ds["train"][0])

# Eval-time helpers (test split):
ex = ds["test"][0]
perception = json.loads(ex["Perception"])
knowledge  = json.loads(ex["Medical knowledge"])
rationale  = json.loads(ex["Rationale"])
print(f"perception items: {len(perception)}")

Anonymity

The dataset is hosted from an anonymous account and the dataset card omits any identifying information about the authors, institution, or project.