I was reading a bit on the developing RayCare OIS, and wondered why an optimization algorithm company would have an interest in developing an enterprise oncology informatics system.
It doesn't take much to realize that oncology informatics is rife with opportunities for applying optimization expertise. Analysis of the flood of data is only the most obvious benefit from expertise in machine learning and statistical inference. But even the bread and butter of oncology informatics--managing daily workflows and data--could benefit from this expertise.
For the data generated by daily workflows to be meaningfully used, the workflows (and supporting infrastructure) must be efficient. Such an infrastructure needs to support workflows involving various actors (both people and systems), as well as a consistent data model shared by the actors to represent the entities participating in the workflows.
The DICOM Information Model for radiotherapy provides a relatively consistent, if somewhat incomplete (yet), model of how data is produced and consumed during RT treatment. Such a data model can be used to help streamline workflows, as a semantically consistent data stream can be used as the input to the fabled prefetcher (see Clunie's zombie apocalypse scenario), in order to ensure the right data is available at the right time. And. if we know enough about the workflows (i.e. what processing needs to be done; what areas of interest are to be reviewed), then we can even prepare this before hand, so when the reviewer picks the next item from the worklist, it is all ready to go.
So if RayCare's OIS can make use of some optimization expertise to build a better autonomous prefetch algorithm (and the associated pre-processing and softcopy presentation state determination algorithms), this would probably be a pretty nifty trick.
But getting all the sources of data to fit in to the DICOM information model, or (even better) fixing the DICOM information model to make it more suited for purpose, seems to be the big hiccup here. Maybe having RayCare also working on the problem, things will begin to advance. That's what free markets do, and we all want free markets, right?
It doesn't take much to realize that oncology informatics is rife with opportunities for applying optimization expertise. Analysis of the flood of data is only the most obvious benefit from expertise in machine learning and statistical inference. But even the bread and butter of oncology informatics--managing daily workflows and data--could benefit from this expertise.
For the data generated by daily workflows to be meaningfully used, the workflows (and supporting infrastructure) must be efficient. Such an infrastructure needs to support workflows involving various actors (both people and systems), as well as a consistent data model shared by the actors to represent the entities participating in the workflows.
The DICOM Information Model for radiotherapy provides a relatively consistent, if somewhat incomplete (yet), model of how data is produced and consumed during RT treatment. Such a data model can be used to help streamline workflows, as a semantically consistent data stream can be used as the input to the fabled prefetcher (see Clunie's zombie apocalypse scenario), in order to ensure the right data is available at the right time. And. if we know enough about the workflows (i.e. what processing needs to be done; what areas of interest are to be reviewed), then we can even prepare this before hand, so when the reviewer picks the next item from the worklist, it is all ready to go.
So if RayCare's OIS can make use of some optimization expertise to build a better autonomous prefetch algorithm (and the associated pre-processing and softcopy presentation state determination algorithms), this would probably be a pretty nifty trick.
But getting all the sources of data to fit in to the DICOM information model, or (even better) fixing the DICOM information model to make it more suited for purpose, seems to be the big hiccup here. Maybe having RayCare also working on the problem, things will begin to advance. That's what free markets do, and we all want free markets, right?
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