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@@ -9,62 +9,46 @@ size_categories:
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  - 1K<n<10K
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  ---
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- ===========================================
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- MEDIQA-Chat 2023 Training/Validation Data
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- ===========================================
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-
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- Task A:
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- =======
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  The training set consists of 1,201 pairs of conversations and associated section headers and contents.
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  The validation set consists of 100 pairs of conversations and their summaries.
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-
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  The full list of normalized section headers:
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-
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- 1. fam/sochx [FAMILY HISTORY/SOCIAL HISTORY]
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- 2. genhx [HISTORY of PRESENT ILLNESS]
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- 3. pastmedicalhx [PAST MEDICAL HISTORY]
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- 4. cc [CHIEF COMPLAINT]
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- 5. pastsurgical [PAST SURGICAL HISTORY]
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- 6. allergy
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- 7. ros [REVIEW OF SYSTEMS]
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- 8. medications
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- 9. assessment
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- 10. exam
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- 11. diagnosis
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- 12. disposition
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- 13. plan
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- 14. edcourse [EMERGENCY DEPARTMENT COURSE]
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- 15. immunizations
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- 16. imaging
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- 17. gynhx [GYNECOLOGIC HISTORY]
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- 18. procedures
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- 19. other_history
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- 20. labs
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-
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-
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- Task B:
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- =======
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  The training set consists of 67 pairs of conversations and full notes. The validation set includes 20 pairs of conversations and clinical notes.
 
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- 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 :
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-
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- | note_division | section_headers
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- ---------------------------------------------------------------------------
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- | subjective | chief complaint, history of present illness, hpi, subjective
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- ---------------------------------------------------------------------------
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- | objective_exam | physical exam, exam
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- ---------------------------------------------------------------------------
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- | objective_results | results, findings
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- ---------------------------------------------------------------------------
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- | assessment_and_plan | assessment, plan
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  Depending on the encounter, objective_exam and objective_results may not be relevant.
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  We encourage review the sample data as well as the evaluation script to understand the best demarkation headers for your generated note.
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-
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- Task C:
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- =======
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  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.
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-
 
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  - 1K<n<10K
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  ---
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+ # MEDIQA-Chat 2023 Training/Validation Data
 
 
 
 
 
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+ # Task A
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  The training set consists of 1,201 pairs of conversations and associated section headers and contents.
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  The validation set consists of 100 pairs of conversations and their summaries.
17
 
 
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  The full list of normalized section headers:
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+ 1. fam/sochx [FAMILY HISTORY/SOCIAL HISTORY]
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+ 2. genhx [HISTORY of PRESENT ILLNESS]
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+ 3. pastmedicalhx [PAST MEDICAL HISTORY]
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+ 4. cc [CHIEF COMPLAINT]
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+ 5. pastsurgical [PAST SURGICAL HISTORY]
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+ 6. allergy
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+ 7. ros [REVIEW OF SYSTEMS]
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+ 8. medications
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+ 9. assessment
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+ 10. exam
29
+ 11. diagnosis
30
+ 12. disposition
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+ 13. plan
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+ 14. edcourse [EMERGENCY DEPARTMENT COURSE]
33
+ 15. immunizations
34
+ 16. imaging
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+ 17. gynhx [GYNECOLOGIC HISTORY]
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+ 18. procedures
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+ 19. other_history
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+ 20. labs
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+
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+ # Task B
 
 
 
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  The training set consists of 67 pairs of conversations and full notes. The validation set includes 20 pairs of conversations and clinical notes.
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+ 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:
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+ > | note_division | section_headers
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+ > | subjective | chief complaint, history of present illness, hpi, subjective
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+ > | objective_exam | physical exam, exam
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+ > | objective_results | results, findings
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+ > | assessment_and_plan | assessment, plan
 
 
 
 
 
 
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  Depending on the encounter, objective_exam and objective_results may not be relevant.
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  We encourage review the sample data as well as the evaluation script to understand the best demarkation headers for your generated note.
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+ # Task C
 
 
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  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.