Update README.md

README.md

@@ -13,6 +13,32 @@ tags:
 - Segmentation
 ---
 
-# Model Card for {{ SentenceSegmenter-MIMIC | default("Model ID", true) }}
+# Model Card for SentenceSegmenter-MIMIC
 
+<!-- Provide a quick summary of what the model is/does. [Optional] -->
+This model is used for sentence segmentation of MIMIC-III notes. It takes the clinical text as input and predict BIO tagging, where B indicates the Beginning of a sentence, I represents Inside of a sentence, and O denotes Outside of a sentence. More details of this model is in the paper &#34;Automatic sentence segmentation of clinical record narratives in real-world data&#34;. The smaple code of using this model is at &#34;https://github.com/dongfang91/sentence_segmenter/tree/main/baseline&#34;  
 
+Out segmentation model is based on &#34;microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext&#34;, and we trained on MIMIC-III notes for a sequence labeling (token classification) task.
+
+
+# Model Details
+
+## Model Description
+
+<!-- Provide a longer summary of what this model is/does. -->
+This model is used for sentence segmentation of MIMIC-III notes. It takes the clinical text as input and predict BIO tagging, where B indicates the Beginning of a sentence, I represents Inside of a sentence, and O denotes Outside of a sentence. More details of this model is in the paper [Automatic sentence segmentation of clinical record narratives in real-world data](https://aclanthology.org/2024.emnlp-main.1156/). The smaple code of using this model is at [github](https://github.com/dongfang91/sentence_segmenter/tree/main/baseline) 
+
+Out segmentation model is based on [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext), and we trained on MIMIC-III notes for a sequence labeling (token classification) task.
+
+
+- **Model type:** token classification model
+- **Language(s) (NLP):** en
+- **Parent Model:** [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext)
+- **Resources for more information:** More information needed
+[GitHub Repo](https://github.com/dongfang91/sentence_segmenter/tree/main/baseline)
+
+
+# Citation
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+Dongfang Xu, Davy Weissenbacher, Karen O’Connor, Siddharth Rawal, and Graciela Gonzalez Hernandez. 2024. [Automatic sentence segmentation of clinical record narratives in real-world data](https://aclanthology.org/2024.emnlp-main.1156/). In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 20780–20793, Miami, Florida, USA. Association for Computational Linguistics.