Papers by Ofer Shapira
Improving Precancerous Case Characterization via Transformer-based Ensemble Learning (2022.emnlp-industry)
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Yizhen Zhong, Jiajie Xiao, Thomas Vetterli, Mahan Matin, Ellen Loo, Jimmy Lin, Richard Bourgon, Ofer Shapira
| Challenge: | Application of natural language processing (NLP) to cancer pathology reports has been focused on detecting cancer cases, ignoring precancerous cases. |
| Approach: | They developed transformer-based deep neural network NLP models to perform the CRC phenotyping with the goal of extracting precancerous lesion attributes and distinguishing cancer and precancirous cases. |
| Outcome: | The proposed model achieves 0.914 macro-F1 scores for classifying patients into negative, non-advanced adenoma, advanced adénoma and CRC. |