Update README.md

README.md

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 # Dataset Card: SIMORD (Simulated Medical Order Extraction Dataset)
 
-## 1. Dataset Summary
+Medical order extraction involves identifying and structuring various medical orders —such as medications, imaging studies, lab tests, and follow-ups— based on doctor-patient conversations. Previous efforts have focused on extracting entities and relations from clinical texts. 
+
+This shared task seeks to develop effective solutions for improving clinical documentation, reducing the burden on providers, and ensuring critical patient information is accurately captured from long conversations. 
+
+The input dialogues are sourced from a combination of existing conversational datasets (e.g., ACI-Bench [1], PriMock57 [2]), and structured lists of medical orders are created by medical annotators.
+
+## Dataset Summary
 
 - **Name**: SIMORD  
 - **Full name / acronym**: SIMulated ORDer Extraction  
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 Follow the steps in `https://github.com/jpcorb20/mediqa-oe` to merge transcripts from ACI-Bench and Primock57 into the annotation files provided in the repo.
 
-## 4. Data Fields / Format
+## Data Fields / Format
 
 **Input fields**:  
   - **transcript** (dict of list): the doctor-patient consultation transcript as dict of three lists using those keys:
@@ -69,4 +75,9 @@ If you use this dataset, please cite:
       author={Corbeil, Jean-Philippe and Abacha, Asma Ben and Michalopoulos, George and Swazinna, Phillip and Del-Agua, Miguel and Tremblay, Jerome and Daniel, Akila Jeeson and Bader, Cari and Cho, Yu-Cheng and Krishnan, Pooja and others},
       journal={arXiv preprint arXiv:2507.05517},
       year={2025}
-    }
+    }
+
+## References
+
+[1] Aci-bench: a Novel Ambient Clinical Intelligence Dataset for Benchmarking Automatic Visit Note Generation. Wen-wai Yim, Yujuan Fu, Asma Ben Abacha, Neal Snider, Thomas Lin, Meliha Yetisgen. Nature Scientific Data, 10, 586 (2023). 
+[2] PriMock57: A Dataset Of Primary Care Mock Consultations. Alex Papadopoulos Korfiatis, Francesco Moramarco, Radmila Sarac, and Aleksandar Savkov. 2022. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 588–598, Dublin, Ireland.