An Introduction to ML for Healthcare Organization on Google Cloud
When it comes to preparing your healthcare organization for ML workflows in Google Cloud, there are a few hurdles to overcome, namely: Do you have enough data available? Is it formatted correctly in a way you can use it? And, how are you allowed to access it? While these first steps may require data aggregation, parsing and anonymization, this article will assume you’ve ported your data to the cloud – maybe using Google Cloud Healthcare’s FHIR, HL7v2, or DICOM integrations – and are ready to glean some valuable information from it.