---
configs:
- config_name: virtassist
  default: true
  data_files:
  - split: train
    path: virtassist/train.parquet
  - split: valid
    path: virtassist/valid.parquet
  - split: test1
    path: virtassist/test1.parquet
  - split: test2
    path: virtassist/test2.parquet
  - split: test3
    path: virtassist/test3.parquet
- config_name: aci
  data_files:
  - split: train
    path: aci/train.parquet
  - split: valid
    path: aci/valid.parquet
  - split: test1
    path: aci/test1.parquet
  - split: test2
    path: aci/test2.parquet
  - split: test3
    path: aci/test3.parquet
- config_name: virtscribe
  data_files:
  - split: train
    path: virtscribe/train.parquet
  - split: valid
    path: virtscribe/valid.parquet
  - split: test1
    path: virtscribe/test1.parquet
  - split: test2
    path: virtscribe/test2.parquet
  - split: test3
    path: virtscribe/test3.parquet
license: cc-by-4.0
task_categories:
- text-generation
tags:
- medical
- clinical
- dialogue
pretty_name: ACI-Bench
---

# ACI-Bench


HuggingFace upload of ACI-Bench, which evaluates a model's ability to convert clinical dialogue into structured clinical notes. This repo contains only the core benchmarking data. The full dataset is available on HuggingFace [here](https://huggingface.co/datasets/mkieffer/ACI-Bench-MedARC). If used, please cite the original authors using the citation below.



## Dataset Details

|                        | train | valid | test1 | test2 | test3 |
| ---------------------- | ----: | ----: | ----: | ----: | ----: |
| **aci**                |    35 |    11 |    22 |    22 |    22 |
| **virtassist**         |    20 |     5 |    10 |    10 |    10 |
| **virtscribe**         |    12 |     4 |     8 |     8 |     8 |
| **total**  |    67 |    20 |    40 |    40 |    40 |


### Dataset Description

The dataset consists of different subsets capturing different clinical workflows

1) ambient clinical intelligence (`aci`): doctor-patient dialogue
2) virtual assistant (`virtassist`): doctor-patient dialogue with queues to trigger Dragon Copilot, e.g., "hey, dragon. show me the chest x-ray"
3) virtual scribe (`virtscribe`): doctor-patient dialogue with a short dictation from the doctor about the patient at the very beginning

### Dataset Sources 

- **GitHub:** https://github.com/wyim/aci-bench
- **Paper:** https://www.nature.com/articles/s41597-023-02487-3


### Direct Use

```python
from datasets import load_dataset

SUBSETS = ["virtassist", "virtscribe", "aci"]
SPLITS = ["train", "valid", "test1", "test2", "test3"]

if __name__ == "__main__":
    # ---------------------------------------------------------------------
    # 1) Load ONE subset (config) with ALL splits
    # ---------------------------------------------------------------------
    virtassist_all = load_dataset("mkieffer/ACI-Bench", name="virtassist")

    # ---------------------------------------------------------------------
    # 2) Load ONE subset (config) with ONE split
    # ---------------------------------------------------------------------
    virtassist_train = load_dataset("mkieffer/ACI-Bench", name="virtassist", split="train")

    # ---------------------------------------------------------------------
    # 3) Load TWO subsets (configs), all splits for each
    # ---------------------------------------------------------------------
    two_subsets = {
        "virtassist": load_dataset("mkieffer/ACI-Bench", name="virtassist"),
        "aci": load_dataset("mkieffer/ACI-Bench", name="aci"),
    }

    # ---------------------------------------------------------------------
    # 4) Load ALL subsets (virtassist, virtscribe, aci), all splits each
    # ---------------------------------------------------------------------
    all_subsets = {subset: load_dataset("mkieffer/ACI-Bench", name=subset) for subset in SUBSETS}
    aci_all = all_subsets["aci"]  # DatasetDict
    aci_train = aci_all["train"]  # Dataset
    aci_valid = aci_all["valid"]

    # ---------------------------------------------------------------------
    # 5) Load multiple splits at once
    # ---------------------------------------------------------------------
    # load each split, concatenated
    aci_all_test_concat = load_dataset("mkieffer/ACI-Bench", name="aci", split=["train", "test1+test2+test3"])
    
    # load each split separately
    aci_all_test_separate = load_dataset("mkieffer/ACI-Bench", name="aci", split=["train", "test1", "test2", "test3"])
```


## Citation 

```
@article{aci-bench,
  author = {Wen{-}wai Yim and
                Yujuan Fu and
                Asma {Ben Abacha} and
                Neal Snider and Thomas Lin and Meliha Yetisgen},
  title = {ACI-BENCH: a Novel Ambient Clinical Intelligence Dataset for Benchmarking Automatic Visit Note Generation},
  journal = {Nature Scientific Data},
  year = {2023}
}
```