Update README.md

README.md

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-Given a conversation between a doctor and patient, participants are tasked with producing a clinical note summarizing the conversation with one or multiple note sections (e.g. Assessment, Past Medical History, Past Surgical History). 
-The Dialogue2Note Summarization task will focus on the generation of specific sections.
+===========================================
+MEDIQA-Chat 2023 Training/Validation Data
+===========================================
+
+Task A:
+=======
+
+The training set consists of 1,201 pairs of conversations and associated section headers and contents. 
+The validation set consists of 100 pairs of conversations and their summaries. 
+
+
+The full list of normalized section headers: 
+
+1. fam/sochx [FAMILY HISTORY/SOCIAL HISTORY]
+2. genhx [HISTORY of PRESENT ILLNESS]
+3. pastmedicalhx [PAST MEDICAL HISTORY]
+4. cc [CHIEF COMPLAINT]
+5. pastsurgical [PAST SURGICAL HISTORY]
+6. allergy
+7. ros [REVIEW OF SYSTEMS]
+8. medications
+9. assessment
+10. exam
+11. diagnosis
+12. disposition
+13. plan
+14. edcourse [EMERGENCY DEPARTMENT COURSE]
+15. immunizations
+16. imaging
+17. gynhx [GYNECOLOGIC HISTORY]
+18. procedures
+19. other_history
+20. labs
+
+
+Task B:
+=======
+The training set consists of 67 pairs of conversations and full notes. The validation set includes 20 pairs of conversations and clinical notes. 
+
+Full encounter notes are expected to have at least one of four overall section divisions demarked by the first-occuring of its related section headers :
+
+| note_division | section_headers
+---------------------------------------------------------------------------
+| subjective | chief complaint, history of present illness, hpi, subjective
+---------------------------------------------------------------------------
+| objective_exam | physical exam, exam
+---------------------------------------------------------------------------
+| objective_results | results, findings
+---------------------------------------------------------------------------
+| assessment_and_plan | assessment, plan
+
+Depending on the encounter, objective_exam and objective_results may not be relevant.
+We encourage review the sample data as well as the evaluation script to understand the best demarkation headers for your generated note.
+
+
+Task C:
+=======
+The training set consists of 67 pairs of full doctor-patient conversations and notes and the validation set includes 20 pairs of full conversations and clinical notes (same as Task-B datasets). The Task-A training and validation sets (1,301 pairs) could be used as additional training data. 
+