Abstract
Introduction
Advances in natural language understanding have facilitated the development of Virtual Standardized Patients (VSPs) that may soon rival human patients in conversational ability. We describe herein the development of an artificial intelligence (AI) system for VSPs enabling students to practice their history taking skills.
Methods
Our system consists of (1) Automated Speech Recognition (ASR), (2) hybrid AI for question identification, (3) classifier to choose between the two systems, and (4) automated speech generation. We analyzed the accuracy of the ASR, the two AI systems, the classifier, and student feedback with 620 first year medical students from 2018 to 2021.
Results
System accuracy improved from ∼75% in 2018 to ∼90% in 2021 as refinements in algorithms and additional training data were utilized. Student feedback was positive, and most students felt that practicing with the VSPs was a worthwhile experience.
Conclusion
We have developed a novel hybrid dialogue system that enables artificially intelligent VSPs to correctly answer student questions at levels comparable with human SPs. This system allows trainees to practice and refine their history-taking skills before interacting with human patients.
Disclosure statement
The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.
Glossary
Virtual Standardized Patient: Avatar representation of a human standardized patient that can communicate using natural language.
Natural Language Understanding: The ability of a computing device to understand typical human speech.
Automated Speech Recognition: Any computing system that allows users to speak as a means of data input as opposed to traditional devices such as mice and keyboards.
Additional information
Funding
Notes on contributors
Kellen R. Maicher
Kellen Maicher, MS, MFA, is a Learning and Development Consultant for The James Cancer Hospital and Solove Research Institute and Coordinator for the Ohio State University EdTech Incubator. His research interests include user experience design for virtual reality and affective virtual human development.
Adam Stiff
Adam Stiff was a PhD student in the Department of Computer Science and Engineering at Ohio State University when this work was completed. He is currently employed as an NLP Scientist at Infoscitex Corporation, working on dialogue system applications in the defense sector.
Marisa Scholl
Marisa Scholl, BS, is a Research Data Analyst in the Department of Obstetrics and Gynecology at The Ohio State University.
Michael White
Michael White, PhD, is a Professor in the Department of Linguistics. His primary research interests are in natural language generation and dialogue systems.
Eric Fosler-Lussier
Eric Fosler-Lussier, PhD, is the John Makhoul Professor and Associate Chair of Computer Science and Engineering. His research interests are in technology for understanding spoken language.
William Schuler
William Schuler, PhD, is a Professor in the Department of Linguistics at the Ohio State University. His research interests include computational psycholinguistics and computational cognitive modeling.
Prashant Serai
Prashant Serai was a PhD student in the Department of Computer Science and Engineering, The Ohio State University.
Vishal Sunder
Vishal Sunder was a PhD student in the Department of Computer Science and Engineering, The Ohio State University.
Hannah Forrestal
Hannah Forrestal was an Undergraduate student in Neuroscience at The Ohio State University.
Lexi Mendella
Lexi Mendella was an Undergraduate student in Biology at The Ohio State University.
Mahsa Adib
Mahsa Adib was an Undergraduate student in Biology at The Ohio State University.
Camille Bratton
Camille Bratton was a Medical Student at the University of Toledo, College of Medicine and Life Sciences.
Kevin Lee
Kevin Lee was a Master's student in the Department of Computer Science at Purdue University.
Douglas R. Danforth
Douglas Danforth, PhD, is a Professor in the Department of Obstetrics and Gynecology at The Ohio State University College of Medicine. His research interests involve using virtual patients and virtual reality for medical education.