TNM-Classifier

Overview

TNM-Classifier is a model based on BERT designed to predict the TNM classification of cancer from radiology reports of lung cancer patients. This model is based on the NTCIR-17 MedNLP-SC Radiology Report Subtask (MedTxt-RR) and has been retrained using the corpus released in MedTxt-RR. This model is for the model in this github.

Model Features

Model Architecture: JMedRoBERTa (manbyo-wordpiece)
Training Data: MedTxt-RR corpus
Use Case: TNM classification of lung cancer (predicting tumor size, lymph node involvement, and distant metastasis)

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Model size

0.1B params

Tensor type

F32

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