Update README.md

README.md

@@ -37,4 +37,112 @@ configs:
     path: virtscribe/test2.parquet
   - split: test3
     path: virtscribe/test3.parquet
----
+---
+
+# ACI-Bench
+
+
+HuggingFace upload of ACI-Bench, which evaluates a model's ability to convert clinical dialogue into structured clinical notes. This dataset includes the [benchmark itself](https://huggingface.co/datasets/mkieffer/ACI-Bench), as well as data from ablation studies testing different transcription methods. If used, please cite the original authors using the citation below.
+
+
+
+## Dataset Details
+
+
+| subset     | transcript_version | train | valid | test1 | test2 | test3 | Total |
+| ---------- | ------------------ | ----- | ----- | ----- | ----- | ----- | ----- |
+| aci        | asr                | 35    | 11    | 22    | 22    | 22    | 112   |
+| aci        | asrcorr            | 35    | 11    | 22    | 22    | 22    | 112   |
+| aci        | humantrans         | 0     | 0     | 0     | 0     | 0     | 0     |
+| virtassist | asr                | 0     | 0     | 0     | 0     | 0     | 0     |
+| virtassist | asrcorr            | 0     | 0     | 0     | 0     | 0     | 0     |
+| virtassist | humantrans         | 20    | 5     | 10    | 10    | 10    | 55    |
+| virtscribe | asr                | 12    | 4     | 8     | 8     | 8     | 40    |
+| virtscribe | asrcorr            | 0     | 0     | 0     | 0     | 0     | 0     |
+| virtscribe | humantrans         | 12    | 4     | 8     | 8     | 8     | 40    |
+| ALL        | ALL                | 114   | 35    | 70    | 70    | 70    | 359   |
+
+### 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
+
+There are three different transcription versions:
+1) `asr`: machine-transcribed
+2) `asrcorr`: human corrections to `asr`, for example: "nonsmile" in D2N081 --> "non-small" in ACI006
+3) `humantrans`: transcribed by a human
+
+The subsets have the following transcription versions
+1) `aci`: `asr` and `asrcorr`
+2) `virtassist`: `humantrans` only
+3) `virtscribe`: `asr` and `humantrans`
+
+
+### 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-MedARC", name="virtassist")
+
+    # ---------------------------------------------------------------------
+    # 2) Load ONE subset (config) with ONE split
+    # ---------------------------------------------------------------------
+    virtassist_train = load_dataset("mkieffer/ACI-Bench-MedARC", name="virtassist", split="train")
+
+    # ---------------------------------------------------------------------
+    # 3) Load TWO subsets (configs), all splits for each
+    # ---------------------------------------------------------------------
+    two_subsets = {
+        "virtassist": load_dataset("mkieffer/ACI-Bench-MedARC", name="virtassist"),
+        "aci": load_dataset("mkieffer/ACI-Bench-MedARC", name="aci"),
+    }
+
+    # ---------------------------------------------------------------------
+    # 4) Load ALL subsets (virtassist, virtscribe, aci), all splits each
+    # ---------------------------------------------------------------------
+    all_subsets = {subset: load_dataset("mkieffer/ACI-Bench-MedARC", 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-MedARC", name="aci", split=["train", "test1+test2+test3"])
+    
+    # load each split separately
+    aci_all_test_separate = load_dataset("mkieffer/ACI-Bench-MedARC", name="aci", split=["train", "test1", "test2", "test3"])
+```
+
+
+## Citation 
+
+```bibtex
+@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}
+}
+```