Create README.md

README.md

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+---
+task_categories:
+- question-answering
+language:
+- en
+tags:
+- medical
+pretty_name: LiveQAMedical
+size_categories:
+- n<1K
+---
+
+# Dataset Card for LiveQA Medical from TREC 2017
+
+The LiveQA'17 medical task focuses on consumer health question answering. Consumer health questions were received by the U.S. National Library of Medicine (NLM). 
+The dataset consists of constructed medical question-answer pairs for training and testing, with additional annotations that can be used to develop question analysis and question answering systems.  
+
+Please refer to our overview paper for more information about the constructed datasets and the LiveQA Track: 
+
+Asma Ben Abacha, Eugene Agichtein, Yuval Pinter & Dina Demner-Fushman. Overview of the Medical Question Answering Task at TREC 2017 LiveQA. TREC, Gaithersburg, MD, 2017 (https://trec.nist.gov/pubs/trec26/papers/Overview-QA.pdf). 
+ 
+
+**Homepage:** [https://github.com/abachaa/LiveQA_MedicalTask_TREC2017](https://github.com/abachaa/LiveQA_MedicalTask_TREC2017)
+
+## Medical Training Data
+
+Currently, this part of the dataset is not integrated with huggingface.
+You can download the pre-processed jsonl that I have uploaded in the files tab instead.
+
+The dataset provides 634 question-answer pairs for training: 
+
+	1) TREC-2017-LiveQA-Medical-Train-1.xml => 388 question-answer pairs corresponding to 200 NLM questions. 
+	Each question is divided into one or more subquestion(s). Each subquestion has one or more answer(s). 
+	These question-answer pairs were constructed automatically and validated manually.
+
+	2) TREC-2017-LiveQA-Medical-Train-2.xml => 246 question-answer pairs corresponding to 246 NLM questions.
+	Answers were retrieved manually by librarians. 
+
+The datasets are not exhaustive with regards to subquestions, i.e., some subquestions might not be annotated. 
+Additional annotations are provided for both (i) the Focus and (ii) the Question Type used to define each subquestion. 
+23 question types were considered (e.g. Treatment, Cause, Diagnosis, Indication, Susceptibility, Dosage) related to four focus categories: Disease, Drug, Treatment and Exam.
+
+## Medical Test Data
+
+Test split can be easily downloaded via huggingface.
+
+  Test questions cover 26 question types associated with five focus categories. 
+  Each question includes one or more subquestion(s) and at least one focus and one question type. 
+  Reference answers were selected from trusted resources and validated by medical experts. 
+  At least one reference answer is provided for each test question, its URL and relevant comments. 
+  Question paraphrases were created by assessors and used with the reference answers to judge the participants' answers.  
+
+```
+If you use these datasets, please cite paper: 
+
+	@inproceedings{LiveMedQA2017,
+	  author    = {Asma {Ben Abacha} and Eugene Agichtein and Yuval Pinter and Dina Demner{-}Fushman}, 
+	  title     = {Overview of the Medical Question Answering Task at TREC 2017 LiveQA}, 
+	  booktitle = {TREC 2017},
+	  year      = {2017}
+	}
+```