Gregory Finley, Erik Edwards, Amanda Robinson, Michael Brenndoerfer, Najmeh Sadoughi, James Fone, Nico Axtmann, Mark Miller, David Suendermann-Oeft
| Challenge: | a medical scribe is a clinical professional who charts patient–physician encounters in real time. |
| Approach: | They propose to use multiple speech and language technologies to create an automated medical scribe. |
| Outcome: | a medical scribe can be used as an alternative to human scribes or as an assistive tool for physicians . the system relies on multiple speech and language technologies, including speaker diarization, medical speech recognition, knowledge extraction, and natural language generation. |
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| Challenge: | a system that extracts pertinent medical information from dialogues between clinicians and patients is proposed . entering data into EMRs is currently slow and error-prone, and clinicians spend up to 50% of their time on data entry. |
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| Challenge: | Medical doctors spend 52 to 102 minutes per day writing clinical notes from patient encounters. |
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Krishanu Das Baksi, Elijah Soba, John J Higgins, Ravi Saini, Jaden Wood, Jane Cook, Jack I Scott, Nirmala Pudota, Tim Weninger, Edward Bowen, Sanmitra Bhattacharya
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User-Driven Research of Medical Note Generation Software (2022.naacl-main)
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Tom Knoll, Francesco Moramarco, Alex Papadopoulos Korfiatis, Rachel Young, Claudia Ruffini, Mark Perera, Christian Perstl, Ehud Reiter, Anya Belz, Aleksandar Savkov
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Applications of Natural Language Processing in Clinical Research and Practice (N19-5)
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| Challenge: | a tutorial on clinical NLP will introduce students and experts to the field . a focus will be on the use of clinical Nlp in clinical research and practice . |
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A French Medical Conversations Corpus Annotated for a Virtual Patient Dialogue System (2020.lrec-1)
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| Challenge: | Existing methods for creating virtual patient dialogue systems require large data specific to the language, domain and clinical cases studied. |
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Alignment Annotation for Clinic Visit Dialogue to Clinical Note Sentence Language Generation (2020.lrec-1)
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| Challenge: | Despite advances in natural language processing, converting a clinic visit conversation into a clinical note is a largely unexplored area of research. |
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