This is the source code for MetaEHR, which is a Python package for few-shot clinical prediction problems, including time-associated prediction targets and time-independent prediction targets. Code will be uploaded soon.
The time-associated algorithm is the implementation of our work TAML: Time-associated Meta Learning for Clinical Prediction. The time-independent algorithm can be any of following meta learning algorithm: MAML, ProtoNet.
- Problem type
- Time-associated targets. For example, mortality time, ICU length of stay.
- Time-independent targets. For example, AKI, pneumonia.
- Input file type
- Single file. For example, preoperative data, flowsheet data, time-series data.
- Multifple files. For example, all of the above data types from the same patients.
- Other required files
- Outcome file, which serves as candidate for meta-tasks.
- Predictive target file, which is the true few-shot target.
- (Optional) Validation target, which will be randomly chose if not specified.