Machine Learning , some thoughts

Dr Evelyn Hovenga ehovenga at
Tue Jun 26 12:10:05 EDT 2018

Bert nurses think like you, they need to view every patient within the context of the person's response to their complaint, injury, procedures performed or treatments provide and the person's individual social network, family commitments, lifestyle, home and workplace environments,  location exposures (current and/or past) etc.  We should be able to collect and store information about these aspects in lifelong EHRs.


-----Original Message-----
From: openEHR-clinical <openehr-clinical-bounces at> On Behalf Of Bert Verhees
Sent: Wednesday, 27 June 2018 12:17 AM
To: Stefan Sauermann <sauermann at>; For openEHR clinical discussions <openehr-clinical at>
Subject: Re: Machine Learning , some thoughts

On 26-06-18 14:35, Stefan Sauermann wrote:
> Dear Bert, all!
> Sorry if this consumes excess bandwith, feel free to delete.
> The case you describe clearly provides a sound reason why "generic 
> archetypes will remain necessary".
> I agree completely. This use case must always be satisfied.
> It does not include automated processing at the receiving end. The 
> receiving party must read the information and decide what to do, using 
> their human brain cells, no 100% reliable computer aided decision 
> support (as in medical devices).
> In this use case, I see no difference between:
> - transmitting information within a "generic archetype"
> - transmitting the same information in unstructured free text.
> Both technologies provide a useful solution for the use case.
>  - So (in my humble view) this specific use case does not demand a 
> "generic archetype". In other words, it needs no archetype at all.
Just a few days ago I heard about Google scanning a great number of files of all kind and format, searching for medical information. The results were quite remarkable.

But unstructured information is not what I am aiming for.

There will be some semantics.
A clinician can indicate that data are from the user story, or from the observation, so, that is already some information.
While talking with the patient, the doctor can measure heartbeat, bloodpressure, saturation, temperature, bloodsugar, even almost without touching de patient. It will be more soon.
Development goes so fast.
And patients can also measure data at home, or at work, or wherever.
Context is also location, patient personal data, time of the day, jet-lag, season of the year, weather conditions, other medical conditions, alcohol consumption, social status

Most of these data are not regarded as relevant in the actual medical condition. So archetypes do not have items for this.

There are two kind of medical data.
a) Medical data which are relevant in the context of a specific medical condition.
b) Medical data of which the relevancy is not yet known in the context of a medical condition, or another medical condition, which maybe is also not known at the moment.

The data of the second kind are also medical data, so why not store them?

Karsten yesterday said, a person at the doctor should be more then a medical complaint. I agree with that. But the current medical practice is not like that.
You go to the doctor with a medical complaint, and you talk about that, the doctor does research in that context, and the software finds some archetypes which fit to that.

But the person should be seen as more then a medical complaint, but as a complex of conditions and lifestyle.
We need generic archetypes which can store machine generated datasets to store information about the whole person, instead of only the medical condition which is subject of conversation.

I believe I am the only person in this list who thinks like that. But that does not matter.

Have a nice day

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