Thermal Image‑Based Temperament Classification by Genetic Algorithm and Adaboost Classifier
سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 95
فایل این مقاله در 8 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JMSI-12-1_004
تاریخ نمایه سازی: 28 تیر 1402
چکیده مقاله:
Background: Temperament (Mizaj) determination is an important stage of diagnosis in Persian
Medicine. This study aimed to evaluate thermal imaging as a reliable tool that can be used instead
of subjective assessments. Methods: The temperament of ۳۴ participants was assessed by a PM
specialist using standardized Mojahedi Mizaj Questionnaire (MMQ) and thermal images of the
wrist in the supine position, the back of the hand, and their whole face under supervision of the
physician were recorded. Thirteen thermal features were extracted and a classifying algorithm was
designed based on the genetic algorithm and Adaboost classifier in reference to the temperament
questionnaire. Results: The results showed that the mean temperature and temperature variations
in the thermal images were relatively consistent with the results of MMQ. Among the three body
regions, the results related to the image from Malmas were most consistent with MMQ. By selecting
six of the ۱۳ features that had the most impact on the classification, the accuracy of ۹۴.۷ ± ۱۳.۰,
sensitivity of ۹۵.۷ ± ۱۱.۳, and specificity of ۹۸.۲ ± ۴.۲ were obtained. Conclusions: The thermal
imaging was relatively consistent with standardized MMQ and can be used as a reliable tool for
evaluating warm/cold temperament. However, the results reveal that thermal imaging features may
not be only main features for temperament classification and for more reliable classification, it needs
to add some different features such as wrist pulse features and some subjective characteristics.
کلیدواژه ها:
نویسندگان
Roshanak Ghods
Research Institute for Islamic and Complementary Medicine, School of Persian Medicine, Iran University of Medical Sciences
Vahid Reza Nafisi
Biomedical Engineering Group, Electrical and Information Technology Department, Iranian Research Organization for Science and Technology, Tehran, Iran