This repository describes how to build and run locally the baseline model of the COVID-19 DREAM Challenge. The goal of this DREAM Challenge is to develop models that take as input the electronic health records (EHRs) of a patient and outputs the probability of this patient tested positive for COVID-19.
This baseline model takes 13 features including clinical symptoms and vital signs and refers to research conducted by Feng et al. link This baseline model isn't trained on any real COVID patient data. Each patient is given a risk score based on the presence of the 14 features. A threshold of risk score is chosen basing on 10% test positive rate in Washington state. Patients whose risk scores are above threshold are assigned test-positive probability as 1, otherwise 0.
| Feature | OMOP Code | Domain | Threshold |
|---|---|---|---|
| age | - | person | >60 |
| temperature | 3020891 | measurement | >37.5' |
| heart rate | 3027018 | measurement | >100n/min |
| diastolic blood pressure | 3012888 | measurement | >80mmHg |
| systolic blood pressure | 3004249 | measurement | >120mmHg |
| hematocrit | 3023314 | measurement | >52 |
| neutrophils | 3013650 | measurement | >8 |
| lymphocytes | 3004327 | measurement | >4.8 |
| oxygen saturation in artery blood | 3016502 | measurement | <95 |
| cough | 254761 | condition | - |
| pain in throat | 259153 | condition | - |
| headache | 378253 | condition | - |
| fever | 437663 | condition | - |
- Clone this GitHub repository
docker build -t docker.synapse.org/syn12345/my_model:v0.1 example/app
This section describes how to run the model locally, that is, without using the IT infrastructure of the COVID_19 DREAM challenge(need updates).
Learn more about OMOP Synpuf data(need updates)
The Synpuf data are available here. After downloading them, uncompress the archive and place the data folder where it can later be accessed by the dockerized model (see below).(need updates)
Once the baseline model has been dockerized (see above), run the following command to train the model on Synpuf data:
docker run -v <path to data folder>:/data:ro
-v <path to scratch folder>:/scratch:rw
-v <path to output folder>:/output:rw
docker.synapse.org/syn12345/my_model:v0.1 bash /app/COVID_baseline.sh
where
<path to data folder>is the absolute path to the data (e.g./home/charlie/ehr_experiment/synpuf_data/data).<path to scratch folder>is the absolute path to the scratch folder (e.g./home/charlie/ehr_experiment/scratch).<path to output folder>is the absolute path to where the the predictions will be exported (e.g./home/charlie/ehr_experiment/output))
If the docker model runs successfully, the prediction file predictions.csv file will be created in the output folder. This file has two columns: 1) person_id and 2) test-positive probability. Note: make sure the column 2) contains no NA and the values are between 0 and 1.
Please see this Synapse page for instructions on how to make a submission link