| 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 form 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 9,376 of the 10,126 patients who were e
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xamined at the Department of Oral Radiology, Osaka Dental University during the 6 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), i.e., the maxillary sinus, maxillary bones, mandibular bones, temporo-mandibular joint, salivary glands, soft tissues, and others. Radiographic images were classified into 7 types (18 patterns), i.e., normal, radiolucencies of the jaws, radiopacities of the jaws, partly radiolucencies and partly radiopacities of the Jaws, anomaly of skeletal bones, TMJ disorders, lesions of salivary glands, and others. Radiographical findings were most frequently radiolucencies of the jaws, which were observed in 64% of the patients, and inflammation accounted for 86% No changes, which were the next most frequent X-ray findings, 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.
This posterior probability is considered to assist interpretation of X-ray images for medical decision making. Less
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