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RadLex and Standardization of ontology for radiology procedures


(Seng Chan You) #21

@dlrubin, Here’s my model how to use unsupervised deep learning for medical image combined with structured clinical data to predict clinical outcome.
I’m trying to convert medical image into small-size vector representing the the original image, and combine it with other clinical features.

I uploaded the code to [github][1] for building encoder for medical image, and make feature vector from medical image based on radiology CDM. This is totally compatible with other OHDSI tool ecosystem, such as FeatureExtraction package and PatientLevelPrediction package.

I know i need more explanation to show entire process. I can show it in the poster at the OHDSI symposium.
[1]: https://github.com/OHDSI/StudyProtocolSandbox/blob/master/radiologyCovariateExtraction/R/RadiologyCovariateExtraction.R


(Seng Chan You) #22

The details of model architecture and the package for extracting and converting metadata from DICOM to R-CDM file are available at: https://github.com/NEONKID/RCDM-ETL


(Andrew Williams) #23

This would be useful for work we are doing and have planned.


(Andrew Williams) #24

What a wonderful amount of work you’ve done! I would love to find out more about what you are doing with it. I couldn’t get to your poster at the symposium and the posters aren’t available on the OHDSI website yet.


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