Class Distance Weighted Cross-Entropy Loss for Ulcerative Colitis Severity Estimation

• URL: http://arxiv.org/abs/2202.05167v1
• Date: Wed, 9 Feb 2022 18:47:50 GMT
• Title: Class Distance Weighted Cross-Entropy Loss for Ulcerative Colitis Severity Estimation
• Authors: Gorkem Polat, Ilkay Ergenc, Haluk Tarik Kani, Yesim Ozen Alahdab, Ozlen Atug, Alptekin Temizel
• Abstract summary: We propose a novel loss function called class distance weighted cross-entropy (CDW-CE) that respects the order of the classes and takes the distance of the classes into account in calculation of cost. In this study, we propose a novel loss function called class distance weighted cross-entropy (CDW-CE) that respects the order of the classes and takes the distance of the classes into account in calculation of cost.
• Score: 1.957338076370071
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Endoscopic Mayo score and Ulcerative Colitis Endoscopic Index of Severity are commonly used scoring systems for the assessment of endoscopic severity of ulcerative colitis. They are based on assigning a score in relation to the disease activity, which creates a rank among the levels, making it an ordinal regression problem. On the other hand, most studies use categorical cross-entropy loss function, which is not optimal for the ordinal regression problem, to train the deep learning models. In this study, we propose a novel loss function called class distance weighted cross-entropy (CDW-CE) that respects the order of the classes and takes the distance of the classes into account in calculation of cost. Experimental evaluations show that CDW-CE outperforms the conventional categorical cross-entropy and CORN framework, which is designed for the ordinal regression problems. In addition, CDW-CE does not require any modifications at the output layer and is compatible with the class activation map visualization techniques.

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