Korean Anaphora Recognition System to Develop Healthcare Dialogue-Type Agent / 대한의료정보학회지

OBJECTIVES: Anaphora recognition is a process to identify exactly which noun has been used previously and relates to a pronoun that is included in a specific sentence later. Therefore, anaphora recognition is an essential element of a dialogue agent system. In the current study, all the merits of rule-based, machine learning-based, semantic-based anaphora recognition systems were combined to design and realize a new hybrid-type anaphora recognition system with an optimum capacity. METHODS: Anaphora recognition rules were encoded on the basis of the internal traits of referred expressions and adjacent contexts to realize a rule-based system and to serve as a baseline. A semantic database, related to predicate instances of sentences including referred expressions, was constructed to identify semantic co-relationships between the referent candidates (to which semantic tags were attached) and the semantic information of predicates. This approach would upgrade the anaphora recognition system by reducing the number of referent candidates. Additionally, to realize a machine learning-based system, an anaphora recognition model was developed on the basis of training data, which indicated referred expressions and referents. The three methods were further combined to develop a new single hybrid-based anaphora recognition system. RESULTS: The precision rate of the rule-based systems was 54.9%. However, the precision rate of the hybrid-based system was 63.7%, proving it to be the most efficient method. CONCLUSIONS: The hybrid-based method, developed by the combination of rule-based and machine learning-based methods, represents a new system with enhanced functional capabilities as compared to other pre-existing individual methods.

Medical Jargon Used in Health Care Communication of Family Physician / 가정의학회지

BACKGROUND: When physicians use the medical terms difficult to understand the meaning, patients regard it as an authority of the physician. It has negative influence on physician-patient relationship and hinders delivering accurate meaning to the patient. The purpose of this research is to investigate what kind of medical terms which meaning is difficult to understand (medical jargon) are used in medical interviews and survey the patients' understanding of the medical terms. METHODS: In the preceding study 67 cases of physicians' interviewing with patient were videotaped in the family medicine clinic of a university hospital and they were transcribed from August, 2005 to January, 2007. For this study 60 cases of the transcribed conversations, which interviewing was completely recorded, were assessed for analyzing the content and frequency of medical jargon. The author selected 10 medical terms used in this study's interviews and surveyed the patients' understanding of the medical terms, who visited the family medicine clinic, by questionnaires. RESULTS: In 26 of 60 interviews one or more medical jargon were used by the physician. In 39 of 73 terms (53.4%) the physicians explained meaning of the medical terms to the patient. 213 patients responded to the questionnaires. More than half (median, 55.4%; range, 11.7 to 75.1%) of the respondents expressed that they 'never know' or 'hardly know' the meaning of the medical terms if it was used without explanation. The scores of level of patients' understanding of 10 medical terms significantly increased according to increasing level of income, but the trend is not statistically significant according to increasing age, difference of sex, and level of education. CONCLUSION: The family physicians used medical jargon in 43.3% of medical interviews, and they explained meaning of the medical terms to the patients for more than half of the terms. More than half of the patients in a university hospital family medicine clinic responded that they never knew or hardly knew meaning of the medical terms if they were used without explanation.