발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.6] A Study on Modeling Explainable Expert Knowledge Based on Diagnosis Process |
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| 논문투고자 |
You-Sang Cho, Key-Sun Choi, Ju-Hyuck Han,Yong-Suk Kim |
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| 논문내용 |
This paper notes that the diagnostic process of asking why the patient's symptoms lead to the doctor'sdiagnostic decision for final treatment is made through questions and answers made at each stage.Accordingly, we present a model that creates a question for each step. This model consists of questionsat each stage by reflecting the flow of clinical diagnosis only by specialists. It was performed to inferthe causal relationship of the diagnostic process and included the analysis process of a specialist toconstruct various tasks. This is a diagnostic decision made by a doctor for each patient's symptoms,which can guarantee the explanability of the data, and an inferential approach is possible. Finally, wecompare and evaluate reports on doctor's questions and answers with reports through manual commentaryby experts. The evaluation uses Visual commonsense reasoning model, VI-bert, and Biobert as baselinemodels. As a result, the average performance of BLEU-1 to 2 was 3.5904, 2.8007, and 3.4627,respectively, and the average performance of Rogue-1, 2, and l was 0.1606, 0.3428, and 0.0797,respectively. This shows that medical knowledge is required for the data in report generation, and canbe viewed as Explainable data that can be applied to models for learning causality. |
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