Designing a virtual patient dialogue system based on terminology-rich resources: Challenges and evaluation
Wedi'i Gadw mewn:
| Cyhoeddwyd yn: | Natural Language Engineering vol. 26, no. 2 (Mar 2020), p. 183 |
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| Awduron Eraill: | , , , |
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Cambridge University Press
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| Mynediad Ar-lein: | Citation/Abstract Full Text Full Text - PDF |
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Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
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MARC
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| 100 | 1 | |a Campillos-Llanos, Leonardo |u LIMSI, CNRS, Université Paris-Saclay, Orsay, France; SATT Paris-Saclay, Orsay, France | |
| 245 | 1 | |a Designing a virtual patient dialogue system based on terminology-rich resources: Challenges and evaluation | |
| 260 | |b Cambridge University Press |c Mar 2020 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Virtual patient software allows health professionals to practise their skills by interacting with tools simulating clinical scenarios. A natural language dialogue system can provide natural interaction for medical history-taking. However, the large number of concepts and terms in the medical domain makes the creation of such a system a demanding task. We designed a dialogue system that stands out from current research by its ability to handle a wide variety of medical specialties and clinical cases. To address the task, we designed a patient record model, a knowledge model for the task and a termino-ontological model that hosts structured thesauri with linguistic, terminological and ontological knowledge. We used a frame- and rule-based approach and terminology-rich resources to handle the medical dialogue. This work focuses on the termino-ontological model, the challenges involved and how the system manages resources for the French language. We adopted a comprehensive approach to collect terms and ontological knowledge, and dictionaries of affixes, synonyms and derivational variants. Resources include domain lists containing over 161,000 terms, and dictionaries with over 959,000 word/concept entries. We assessed our approach by having 71 participants (39 medical doctors and 32 non-medical evaluators) interact with the system and use 35 cases from 18 specialities. We conducted a quantitative evaluation of all components by analysing interaction logs (11,834 turns). Natural language understanding achieved an F-measure of 95.8%. Dialogue management provided on average 74.3 (±9.5)% of correct answers. We performed a qualitative evaluation by collecting 171 five-point Likert scale questionnaires. All evaluated aspects obtained mean scores above the Likert mid-scale point. We analysed the vocabulary coverage with regard to unseen cases: the system covered 97.8% of their terms. Evaluations showed that the system achieved high vocabulary coverage on unseen cases and was assessed as relevant for the task. | |
| 653 | |a Natural language | ||
| 653 | |a French language | ||
| 653 | |a Dictionaries | ||
| 653 | |a Medical research | ||
| 653 | |a Affixes | ||
| 653 | |a Ontology | ||
| 653 | |a Physicians | ||
| 653 | |a Terminology | ||
| 653 | |a Medical personnel | ||
| 653 | |a Thesauri | ||
| 653 | |a Synonyms | ||
| 653 | |a Domains | ||
| 653 | |a Computer simulation | ||
| 653 | |a Medical language | ||
| 653 | |a Computer mediated communication | ||
| 653 | |a Dialogue | ||
| 653 | |a Measures | ||
| 653 | |a Knowledge | ||
| 653 | |a Medical history | ||
| 653 | |a Medical records | ||
| 653 | |a Evaluation | ||
| 653 | |a Rules | ||
| 653 | |a Vocabulary | ||
| 653 | |a Resources | ||
| 653 | |a Variants | ||
| 653 | |a Work skills | ||
| 653 | |a Patients | ||
| 653 | |a Social | ||
| 700 | 1 | |a Thomas, Catherine |u LIMSI, CNRS, Université Paris-Saclay, Orsay, France; SATT Paris-Saclay, Orsay, France | |
| 700 | 1 | |a Bilinski, Éric |u LIMSI, CNRS, Université Paris-Saclay, Orsay, France | |
| 700 | 1 | |a Zweigenbaum, Pierre |u LIMSI, CNRS, Université Paris-Saclay, Orsay, France | |
| 700 | 1 | |a Rosset, Sophie |u LIMSI, CNRS, Université Paris-Saclay, Orsay, France | |
| 773 | 0 | |t Natural Language Engineering |g vol. 26, no. 2 (Mar 2020), p. 183 | |
| 786 | 0 | |d ProQuest |t Psychology Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2370339527/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/2370339527/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2370339527/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |