--- license: other language: - en tags: - clinical - ehr - medical - multimodal - benchmark pretty_name: ClinSeek-Bench size_categories: - 1K Model Risk Prediction Decision Making Overall ClinSeekAgent Curated
Input Δ ClinSeekAgent Curated
Input Δ ClinSeekAgent Curated
Input Δ Closed-source models Claude Opus 4.6 90.781.0+9.7 44.845.9-1.1 63.260.0+3.2 Claude Sonnet 4.6 90.077.5+12.5 35.942.6-6.7 57.556.6+0.9 Open-source models EHR-R1-72B --67.1-- --45.2-- --53.9-- GLM-4.7 75.170.4+4.7 23.138.6-15.5 43.951.3-7.4 Qwen3.5-35B-A3B 84.473.6+10.8 22.029.0-7.0 47.046.8+0.1 Gemma-4-26B-A4B-it 83.578.6+4.9 17.327.8-10.5 43.848.1-4.3 MiniMax M2.5 86.768.4+18.3 21.026.3-5.3 47.343.1+4.2 Kimi K2.5 65.079.9-14.9 19.828.8-9.0 37.949.2-11.3 Qwen3-VL-235B 67.971.0-3.1 19.133.4-14.3 38.648.4-9.8 gpt-oss-120b 75.474.0+1.4 16.622.3-5.7 40.143.0-2.9 MedGemma-27B-it --65.0-- --25.2-- --41.1-- EHR-R1-8B --64.0-- --23.4-- --39.7-- ### Multimodal tasks

Model	Method	CXR: finding presence	CXR: finding enumeration	CXR: change comparison	Mortality (24 h)	Inpatient mortality	Phenotype (CCS groups)	Multimodal overall
Claude Opus 4.6	ClinSeekAgent	78.3	43.6	54.8	92.0	74.4	45.5	62.6
	Curated Input	55.2	31.6	38.0	93.6	69.6	11.5	47.5
	Δ	+23.2	+12.0	+16.8	-1.6	+4.8	+34.0	+15.1
Claude Sonnet 4.6	ClinSeekAgent	79.5	41.3	51.5	64.0	68.8	26.1	54.9
	Curated Input	64.8	29.7	34.7	90.4	70.4	13.8	48.0
	Δ	+14.7	+11.6	+16.8	-26.4	-1.6	+12.3	+6.9
Qwen3.5-35B-A3B	ClinSeekAgent	73.8	34.2	44.4	91.2	74.4	0.3	51.7
	Curated Input	59.1	34.1	30.7	90.4	81.6	0.5	46.9
	Δ	+14.7	+0.2	+13.7	+0.8	-7.2	-0.2	+4.8
Kimi K2.5	ClinSeekAgent	61.4	34.9	43.8	71.2	62.4	12.3	46.9
	Curated Input	56.3	24.7	35.0	91.2	87.2	12.4	47.5
	Δ	+5.1	+10.2	+8.8	-20.0	-24.8	-0.1	-0.6
Qwen3-VL-235B	ClinSeekAgent	70.4	35.7	47.8	79.2	61.6	6.0	49.8
	Curated Input	60.3	21.1	32.8	87.2	72.8	6.6	43.9
	Δ	+10.1	+14.6	+15.0	-8.0	-11.2	-0.6	+5.9
Gemma-4-26B-A4B-it	ClinSeekAgent	78.9	21.6	38.4	65.6	71.2	0.4	44.9
	Curated Input	56.9	21.4	25.4	79.2	60.0	0.0	38.2
	Δ	+22.0	+0.2	+13.0	-13.6	+11.2	+0.4	+6.7

These results show that active evidence acquisition is most helpful when the answer depends on sparse, longitudinal, or multimodal signals that may be missed by fixed curated inputs. The gains are especially clear for risk prediction in the text-only split and for CXR-related multimodal tasks, where models can combine EHR retrieval, image-tool outputs, and task-relevant medical knowledge. ## Files ```text ClinSeek-Bench/ +-- README.md +-- ClinSeek-Bench_text.json +-- ClinSeek-Bench_multimodal.jsonl ``` The paths above are the released metadata paths in this dataset repository. If you clone this dataset next to the ClinSeekAgent repository, reference the metadata as: ```text ClinSeek-Bench/ClinSeek-Bench_text.json ClinSeek-Bench/ClinSeek-Bench_multimodal.jsonl ``` If you use ClinSeekAgent's default local data layout, you may copy or symlink the text manifest to `data/text/ClinSeek-Bench_text.json`. That location is a local workspace convenience, not a released metadata path. ## Reconstructing The Full Benchmark Reconstruction code and detailed instructions are maintained in the ClinSeekAgent GitHub repository: - Code: https://github.com/UCSC-VLAA/ClinSeekAgent - Text data preparation: https://github.com/UCSC-VLAA/ClinSeekAgent/blob/main/docs/ClinSeek-Bench_text_data_prepare.md - Automated Evidence-Seeking text evaluation: https://github.com/UCSC-VLAA/ClinSeekAgent/blob/main/docs/ClinSeek-Bench_text_evaluation.md - Curated Input text evaluation: https://github.com/UCSC-VLAA/ClinSeekAgent/blob/main/docs/ClinSeek-Bench_text_curated_input_evaluation.md - Multimodal data preparation: https://github.com/UCSC-VLAA/ClinSeekAgent/blob/main/docs/ClinSeek-Bench_multimodal_data_prepare.md At a high level: ```bash git clone https://huggingface.co/datasets/UCSC-VLAA/ClinSeek-Bench git clone https://github.com/UCSC-VLAA/ClinSeekAgent.git ``` Then obtain the required official source datasets, prepare local paths, and follow the text and multimodal reconstruction guides above. ## Required Source Data Download clinical source data only from official sources under your own credentialed access and data-use agreements. | Dataset or source | Official source | Used for | | --- | --- | --- | | MIMIC-IV | https://physionet.org/content/mimiciv/ | structured EHR tables | | MIMIC-IV-Note | https://physionet.org/content/mimic-iv-note/ | discharge and radiology notes | | MIMIC-IV-ED | https://physionet.org/content/mimic-iv-ed/ | emergency department tables | | MIMIC-CXR | https://physionet.org/content/mimic-cxr/ | CXR metadata and report text | | MIMIC-CXR-JPG | https://physionet.org/content/mimic-cxr-jpg/ | linked chest X-ray JPG files | | EHRXQA | https://physionet.org/content/ehrxqa/ | source-aligned CXR question-answering rows | | MedMod | https://github.com/nyuad-cai/MedMod | source-aligned ICU/CXR prediction rows | | EHR-R1 / EHR-Bench | https://github.com/MAGIC-AI4Med/EHR-R1 | source benchmark for text-only EHR tasks | ## Validation After cloning ClinSeekAgent, validate the released multimodal metadata without requiring protected assets: ```bash python ClinSeekAgent/scripts/data_build/validate_multimodal_release.py \ --bench-root ClinSeek-Bench \ --input ClinSeek-Bench/ClinSeek-Bench_multimodal.jsonl \ --manifest-only ``` Expected released metadata counts: - 1,800 text-only rows; - 45 text-only EHR subtasks; - 1,563 unique text-only patients; - 989 multimodal rows; - 497 EHRXQA-derived multimodal rows; - 492 MedMod-derived multimodal rows; - 350 unique EHRXQA linked CXR JPG paths; - 477 unique MedMod linked CXR JPG paths; - 356 unique EHRXQA linked CXR report paths. After local reconstruction, the same validation script can also check the materialized runtime assets, including patient DBs, image paths, and report paths. See the ClinSeekAgent reconstruction documentation for the full commands. ## Evaluation Evaluation code and instructions are maintained in the ClinSeekAgent repository: https://github.com/UCSC-VLAA/ClinSeekAgent. After reconstructing the protected runtime assets locally, follow the ClinSeekAgent documentation for Automated Evidence-Seeking evaluation, Curated Input evaluation, and scoring. ## Responsible Use ClinSeek-Bench is for research on clinical evidence seeking. It is not a medical device and must not be used for clinical diagnosis, treatment, triage, or patient management without separate validation, governance, and regulatory review.