With the advances in the information and communications technology, plus the biomedical science technology, medical practices nowadays became more and more complicated and risky. Recently, with the implementation of work-hour restriction policy, physicians’ training hours were greatly shortened. The outcome of medical education that intended to prepare them for future patient care is now facing great challenges. There is a need to pursue an effective and efficient teaching strategy. The advanced Digital Multimedia Technology provided simulation encounters that allow repetitive practices in a safe environment. The success of a simulation encounter relies on human-computer interaction, coupling with correct recognition and interpretation of natural language. In the field of medical professional education, there are two main application areas: 1. Medical interview, from the history taking, data collection to the conclusion of diagnosis and treatment; 2. Training in interview, counseling, and communication.
In order to enable the “machine” understands the natural language used in medical encounters, we collected the words and sentences of dialogues between patients and healthcare personnel. They are either natural language or medical jargon and professional terminology. The latter one is about medical disease, tests, examinations and image studies. As for the natural language, we established “medical trees”those collected spoken materials in machine-readable forms, with Nodes, Antonymy and Part-whole relationship.
Prof. Tsuen-Chiuan Tsai is a Pediatrician who obtained her PhD in Medical Education in University of Calgary in Canada. She is now the President of the Taiwan Society for Simulation in Healthcare (TSSH), and the Vice Dean of Academic Affair in Kaohsiung Medical University, and the Vice Dean of KMU College of Medicine. She has been devoted herself in improving the clinical competency of healthcare personnel through education. Prof. Tsai actively promoted the implementation of OSCE (Objective Structured Clinical Examination), simulation, learning technology and established Virtual Patient Educational System.
Assoc. Prof. Yih-Lon Lin received his M.S. and Ph.D. degrees from Department of Electrical Engineering of National Sun Yat-Sen University, Kaohsiung, Taiwan, in 1999 and 2006, respectively, all in Electrical Engineering. He is currently an associate professor of Department of Information Engineering of I-Shou University. His research interests include machine learning, signal and image processing, machine vision, and multimedia applications.