Papers by Janet Mee
Predicting Item Survival for Multiple Choice Questions in a High-Stakes Medical Exam (2020.lrec-1)
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| Challenge: | Existing methods of pretesting are costly and require a large pool of test questions to be replenished, updated and expanded over time. |
| Approach: | They propose to automatically predict an item's probability to "survive" pretesting by embedding new items within a live exam and analyzing the responses. |
| Outcome: | The proposed method is based on human-produced MCQs for a medical exam and shows that survival is modelled through linguistic features and embedding types and features inspired by information retrieval. |
The USMLE® Step 2 Clinical Skills Patient Note Corpus (2022.naacl-main)
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| Challenge: | Large clinical note corpora are one of the most needed and one of least available resources in biomedical NLP due to patient confidentiality considerations and expert annotation cost. |
| Approach: | They present a corpus of 43,985 clinical patient notes (PNs) written by 35,156 examinees during the USMLE® Step 2 Clinical Skills examination. |
| Outcome: | The corpus of 43,985 clinical patient notes (PNs) written by 35,156 examinees during the high-stakes USMLE® Step 2 Clinical Skills examination is available via a data sharing agreement with NBME . |