| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1995: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1994: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Research Abstract |
Accurate diagnosis of oral lesions can be made only by corn-prehensive evaluation of a large quantity of information including in clinical signs and symptoms, and the past history as well as findings on various examinations including radiographical and histopathological examinations. Clinical experience over many years is needed for a physician to become able to select from a large volume of information and utilize only that which is useful However, if the accumulated information can be classified in a more utilizable and accessible forms and can be quickly referred to concerning the case in question, it would, to some extent, diminish the difference in experience among individual doctors and improve the accuracy of the diagnosis.
We input the age, sex, site of the lesion, disease, and image data of patients as basic data, and calculated the probability of the correct diagnosis in computer-aided medical decision making based on these data. Data of 13,036 of the 15,235 patients who were
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examined at the Department of Oral Radiology, Osaka Dental University during the 8 years between 1987 and 1992 was classified and used as basic data.
Ten disease categories (68 lesions), i.e., inflammation, odontogenic cysts, non-odontogenic cysts, odontogenic tumors, non-odontogenic tumors, malignant tumors, trauma, TMJ disorders, unclassifiable diseases, and others were established. The sites of the lesions were classified into 7 categories (32 sites). Radiographic images were classified into 6 types (18 patterns). Radiographic images were most frequently radiolucencies of the jaws, which were observed in 64% of the patients, and inflammatlon accounted for 86%. No changes, which were the next most frequent radiographic images, were observed in the jaw bones in 14%.
We derived a symptom-disease matrix of intra-osseous lesions from these data and calculated the posterior probability and the statical decision tried to radiographic findings from histopathological type of ameloblastoma (289 cases) from these data and calculated the posterior probability.
The results of posterior probability were almost correct. But, the unusual radiographic finding case was not correct. These posterior probability are considered to assist interpretation of radiographic images for medical decision making. Less
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