تقرير
Towards Interpretable Classification of Leukocytes based on Deep Learning
| العنوان: | Towards Interpretable Classification of Leukocytes based on Deep Learning |
|---|---|
| المؤلفون: | Röhrl, Stefan, Groll, Johannes, Lengl, Manuel, Schumann, Simon, Klenk, Christian, Heim, Dominik, Knopp, Martin, Hayden, Oliver, Diepold, Klaus |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning |
| الوصف: | Label-free approaches are attractive in cytological imaging due to their flexibility and cost efficiency. They are supported by machine learning methods, which, despite the lack of labeling and the associated lower contrast, can classify cells with high accuracy where the human observer has little chance to discriminate cells. In order to better integrate these workflows into the clinical decision making process, this work investigates the calibration of confidence estimation for the automated classification of leukocytes. In addition, different visual explanation approaches are compared, which should bring machine decision making closer to professional healthcare applications. Furthermore, we were able to identify general detection patterns in neural networks and demonstrate the utility of the presented approaches in different scenarios of blood cell analysis. Comment: Presented at the 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH) @ ICML 2023 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2311.14485 |
| رقم الأكسشن: | edsarx.2311.14485 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |