Datasets:

CASE-Bench
/

CASE-Agent-Traj-And-Bench-Partial

Partial, de-identified release — companion data for the paper From Given to Gathered Evidence: Agentic Learning for Longitudinal Medical Reasoning: recorded agent trajectories, RL training prompts, benchmark banks and example preview images for longitudinal medical imaging. Full imaging data is not included (UK Biobank controlled); participant identifiers have been replaced by uniform anonymous IDs (case0001–case4739); the ID mapping exists but is not publicly disclosed, in accordance with UK Biobank requirements. Rendered example/preview images are provided in images_examples/ (figure headers cropped).

The CASE project trains three cooperating clinical-agent personas on longitudinal medical imaging through an agentic harness (multi-turn tool calling; the model plans, calls tools, reads observations and answers):

Anatomist — organ segmentation / volumetry across body stations
Radiologist — cross-visit image comparison (multi-modality, multi-sequence)
Consultant — report-grounded synthesis and claim verification

Path	What
`trajectories/{Anatomist_agent,Radiologist_agent,Consultant_agent}/`	recorded agent trajectories (`agent_caseNNNN.jsonl`) and per-patient annotations (`dense_caseNNNN.json`); Consultant additionally ships `skills_caseNNNN.jsonl`
`rl/verl_train_tool.parquet`	reinforcement-learning prompts (verl parquet, one row per patient-question; 30,604 rows)
`benchmark/`	evaluation question banks: `benchmark.parquet` = current bank (14,795 rows / 482 patients); `test.parquet` and `unified.parquet` = earlier banks; each bank ships its participant ID list
`images_examples/`	rendered preview slices for the benchmark set: per participant × six body stations × baseline/follow-up visits (4,938 images; figure headers cropped)

Formats

Trajectories — JSONL, one question instance per line with the full message list. Image content appears only as relative path references (images/<caseNNNN>/img_*.png); the image files themselves are not included.
Parquet (rl/, benchmark/) — one row per (patient, question); columns:
- data_source — task origin: vista3d_opsd (Anatomist), medpanel_v2_opsd (Radiologist), medboard_opsd (Consultant)
- prompt — full chat template: system message (persona, tool definitions, output-format rules) + user message (question, options, tool-use instructions)
- reward_model — answer key, e.g. {"ground_truth": "D"}
- extra_info — JSON string with patient_id (anonymous case ID), question_idx, question, options, ground_truth, tools_kwargs (patient-scoped tool arguments) and teacher_insight (teacher reasoning notes used for the OPSD distillation signal)
- agent_name — tool_agent (multi-turn tool-calling loop)
Row counts — rl/verl_train_tool.parquet: 30,604 (vista3d 9,788 / medpanel 10,408 / medboard 10,408); benchmark.parquet: 14,795.

No images are embedded in any parquet: image observations are served to the tools at run time and are not part of this release.

Licensing / data access

Built on UK Biobank-derived data under an access-controlled research agreement.

Participant IDs — all participant references use uniform anonymous IDs (case0001–case4739). An ID mapping to the original identifiers exists but is not disclosed on this platform, in accordance with UK Biobank requirements.
Images (images_examples/) — rendered preview images are provided for academic display only; redistribution and commercial use are prohibited.
Complete dataset — the full dataset is not redistributed here; access must be requested through the UK Biobank Access Management System (AMS) to obtain access permission for the returned data.

CASE: Clinical Agents for Seeking Evidence — Agent Trajectories & Benchmarks (De-identified)

Contents

Formats

Licensing / data access