mlsanityData to 7 Oct 2026

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

arXiv 2202.05167 ↗First posted 9 Feb 2022eess.IV cs.AI cs.CVcited by 17

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Abstract (arXiv)

In scoring systems used to measure the endoscopic activity of ulcerative colitis, such as Mayo endoscopic score or Ulcerative Colitis Endoscopic Index Severity, levels increase with severity of the disease activity. Such relative ranking among the scores makes it an ordinal regression problem. On the other hand, most studies use categorical cross-entropy loss function to train deep learning models, which is not optimal for the ordinal regression problem. In this study, we propose a novel loss function, 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 the cost. Experimental evaluations show that models trained with CDW-CE outperform the models trained with conventional categorical cross-entropy and other commonly used loss functions which are designed for the ordinal regression problems. In addition, the class activation maps of models trained with CDW-CE loss are more class-discriminative and they are found to be more reasonable by the domain experts.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Builds on 14 of its 46 references that are in the map. First posted on arXiv 9 Feb 2022.

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14 of 46 references.

References · 14

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  11. 2021Deep Neural Networks for Rank-Consistent Ordinal Regression Based On Conditional Probabilitiescited by 57
  12. 2017Unimodal probability distributions for deep ordinal classificationcited by 28
2 more
  1. 2021Automatic Estimation of Ulcerative Colitis Severity from Endoscopy Videos using Ordinal Multi-Instance Learningcited by 7
  2. 2016A simple squared-error reformulation for ordinal classificationcited by 2

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Citing papers per year: 2022: 1; 2023: 5; 2024: 6; 2025: 5.

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  1. 2023Improving Deep Regression with Ordinal Entropycited by 44
  2. 2023Using Sequences of Life-events to Predict Human Livescited by 27
  3. 2023Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classificationcited by 21
  4. 2023Unimodal Distributions for Ordinal Regressioncited by 9
  5. 2024Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformercited by 7
  6. 2024Class Distance Weighted Cross Entropy Loss for Classification of Disease Severitycited by 7
  7. 2023Ulcerative Colitis Mayo Endoscopic Scoring Classification with Active Learning and Generative Data Augmentationcited by 4
  8. 2024Deep Bayesian Active Learning-to-Rank with Relative Annotation for Estimation of Ulcerative Colitis Severitycited by 3
  9. 2024Ordinal-Aware Calibration for Ordinal Classificationcited by 3
  10. 2024Developing vocal system impaired patient-aimed voice quality assessment approach using ASR representation-included multiple featurescited by 1
  11. 2024Arges: Spatio-Temporal Transformer for Ulcerative Colitis Severity Assessment in Endoscopy Videoscited by 1
  12. 2025Weakly-Supervised Domain Adaptation with Proportion-Constrained Pseudo-Labelingcited by 1
5 more
  1. 2022L-MAE: Masked Autoencoders are Semantic Segmentation Datasets Augmentercited by 0
  2. 2025CLoE: Curriculum Learning on Endoscopic Images for Robust MES Classificationcited by 0
  3. 2025MEGAN: Mixture of Experts for Robust Uncertainty Estimation in Endoscopy Videoscited by 0
  4. 2025Domain Adaptation for Ulcerative Colitis Severity Estimation Using Patient-Level Diagnosescited by 0
  5. 2025AGGRNet: Selective Feature Extraction and Aggregation for Enhanced Medical Image Classificationcited by 0