Overview
A block diagram of the Phase 02 models is provided below. Two of the models use the similar fine-tuning methods, and as such, we provide a demo notebook for fine-tuning, providing extended comments on the code. Additionally, since we employ pretraining before fine-tuning, we include a demo notebook for pretraining. To view the actual source code (*.py
files) used for training and classifying, please refer to the train and classify documentation.
In the table below, we provide a description of the different tasks and architectures of the models.
Model Name |
Task |
Architecture |
Source Code Function |
---|---|---|---|
Lung Findings, Adrenal Findings, or No Findings |
Identify if the report has (i) lung (ii) adrneal, or (iii) or no findings |
MLM based on RoBERTa (🤗) |
|
Lung Recommended Procedure (i.e., Chest CT or Ambiguous Follow- up Recommended) |
Identify if a report with lung has findings recommends (i) a Chest CT follow-up or (ii) some other ambiguous procedure |
MLM based on RoBERTa (🤗) |
|
Comment Extraction |
Identify the portion of the report that contains the findings text |
Question-Answer based
RoBERTa
( |