Medical diagnostic support system is an automatic support system that prevents doctors from unknowingly mis-interpreting medical results. However, it is not an easy task to automate the procedure with high accuracy. Our goal is to construct such a medical diagnostic support system that could improve the overall accuracy of medical diagnoses. As a pilot study, we built a program that automatically answers the medical licensing examination (MLE), in our previous study. MLE involves questions that require the users to pick answers such as disease names or drug names from multiple choices, given the patient information. In our previous study, the program was developed to answer only disease related questions, but we realized that the study will not be complete without deciding optimal drug for patients. For this reason, we attempt to expand this program to answer drug related questions in the current research. The major improvements include vectorizing the words and automizing the construction of rule base. By this, we prevented the tedious task of inputting drug information manually and now it is possible to avoid influences of inconsistent spelling and synonyms by vectorization of words. We managed to increase the accuracy of the previous study up to 56.1%.
|Transactions of the Japanese Society for Artificial Intelligence
|Published - 2018
- Medical diagnosis
- Medical licensing examination
ASJC Scopus subject areas
- Artificial Intelligence