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@@ -37,4 +37,102 @@ configs:
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  path: virtscribe/test2.parquet
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  - split: test3
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  path: virtscribe/test3.parquet
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  path: virtscribe/test2.parquet
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  - split: test3
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  path: virtscribe/test3.parquet
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+ license: cc-by-4.0
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+ task_categories:
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+ - text-generation
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+ tags:
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+ - medical
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+ - clinical
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+ pretty_name: ACI-Bench
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+ ---
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+
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+ # ACI-Bench
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+
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+
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+ HuggingFace upload of ACI-Bench, which evaluates a model's ability to convert clinical dialogue into structured clinical notes. If used, please cite the original authors using the citation below.
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+
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+
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+
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+ ## Dataset Details
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+
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+ | | train | valid | test1 | test2 | test3 |
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+ | ---------------------- | ----: | ----: | ----: | ----: | ----: |
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+ | **aci** | 35 | 11 | 22 | 22 | 22 |
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+ | **virtassist** | 20 | 5 | 10 | 10 | 10 |
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+ | **virtscribe** | 12 | 4 | 8 | 8 | 8 |
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+ | **total** | 67 | 20 | 40 | 40 | 40 |
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+
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+
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+ ### Dataset Description
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+
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+ The dataset consists of different subsets capturing different clinical workflows
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+
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+ 1) ambient clinical intelligence (`aci`): doctor-patient dialogue
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+ 2) virtual assistant (`virtassist`): doctor-patient dialogue with queues to trigger Dragon Copilot, e.g., "hey, dragon. show me the chest x-ray"
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+ 3) virtual scribe (`virtscribe`): doctor-patient dialogue with a short dictation from the doctor about the patient at the very beginning
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+
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+ ### Dataset Sources
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+
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+ - **GitHub:** https://github.com/wyim/aci-bench
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+ - **Paper:** https://www.nature.com/articles/s41597-023-02487-3
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+
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+
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+ ### Direct Use
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ SUBSETS = ["virtassist", "virtscribe", "aci"]
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+ SPLITS = ["train", "valid", "test1", "test2", "test3"]
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+
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+ if __name__ == "__main__":
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+ # ---------------------------------------------------------------------
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+ # 1) Load ONE subset (config) with ALL splits
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+ # ---------------------------------------------------------------------
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+ virtassist_all = load_dataset("mkieffer/ACI-Bench", name="virtassist")
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+
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+ # ---------------------------------------------------------------------
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+ # 2) Load ONE subset (config) with ONE split
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+ # ---------------------------------------------------------------------
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+ virtassist_train = load_dataset("mkieffer/ACI-Bench", name="virtassist", split="train")
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+
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+ # ---------------------------------------------------------------------
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+ # 3) Load TWO subsets (configs), all splits for each
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+ # ---------------------------------------------------------------------
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+ two_subsets = {
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+ "virtassist": load_dataset("mkieffer/ACI-Bench", name="virtassist"),
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+ "aci": load_dataset("mkieffer/ACI-Bench", name="aci"),
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+ }
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+
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+ # ---------------------------------------------------------------------
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+ # 4) Load ALL subsets (virtassist, virtscribe, aci), all splits each
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+ # ---------------------------------------------------------------------
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+ all_subsets = {subset: load_dataset("mkieffer/ACI-Bench", name=subset) for subset in SUBSETS}
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+ aci_all = all_subsets["aci"] # DatasetDict
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+ aci_train = aci_all["train"] # Dataset
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+ aci_valid = aci_all["valid"]
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+
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+ # ---------------------------------------------------------------------
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+ # 5) Load multiple splits at once
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+ # ---------------------------------------------------------------------
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+ # load each split, concatenated
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+ aci_all_test_concat = load_dataset("mkieffer/ACI-Bench", name="aci", split=["train", "test1+test2+test3"])
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+
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+ # load each split separately
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+ aci_all_test_separate = load_dataset("mkieffer/ACI-Bench", name="aci", split=["train", "test1", "test2", "test3"])
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+ ```
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+
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+
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+ ## Citation
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+
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+ ```
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+ @article{aci-bench,
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+   author = {Wen{-}wai Yim and
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+                 Yujuan Fu and
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+                 Asma {Ben Abacha} and
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+                 Neal Snider and Thomas Lin and Meliha Yetisgen},
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+   title = {ACI-BENCH: a Novel Ambient Clinical Intelligence Dataset for Benchmarking Automatic Visit Note Generation},
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+   journal = {Nature Scientific Data},
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+   year = {2023}
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+ }
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+ ```