Fully interpretable deep learning model using IR thermal images for possible breast cancer cases
Breast cancer remains a global health problem requiring effective diagnostic methods for early detection, in order to achieve the World Health Organization's ultimate goal of breast self-examination. A literature review indicates the urgency of improving diagnostic methods and identifies thermo...
محفوظ في:
المؤلفون الرئيسيون: | Mirasbekov, Yerken, Aidossov, Nurduman, Mashekova, Aigerim, Zarikas, Vasilios, Zhao, Yong, Ng, Eddie Yin Kwee, Midlenko, Anna |
---|---|
مؤلفون آخرون: | School of Mechanical and Aerospace Engineering |
التنسيق: | مقال |
اللغة: | English |
منشور في: |
2025
|
الموضوعات: | |
الوصول للمادة أونلاين: | https://hdl.handle.net/10356/184374 |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
An integrated intelligent system for breast cancer detection at early stages using IR images and machine learning methods with explainability
بواسطة: Aidossov, Nurduman, وآخرون
منشور في: (2023) -
Evaluation of integrated CNN, transfer learning, and BN with thermography for breast cancer detection
بواسطة: Aidossov, N., وآخرون
منشور في: (2023) -
Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool
بواسطة: Mukhmetov, Olzhas, وآخرون
منشور في: (2024) -
Early detection of the breast cancer using infrared technology – a comprehensive review
بواسطة: Mashekova, Aigerim, وآخرون
منشور في: (2023) -
Patient/breast-specific detection of breast tumor based on patients’ thermograms, 3D breast scans, and reverse thermal modelling
بواسطة: Mukhmetov, Olzhas, وآخرون
منشور في: (2022)