Machine Learning , some thoughts

Rakesh Biswas rakesh7biswas at
Tue Jun 26 12:24:44 EDT 2018

Doctors too. More here

On Jun 26, 2018 9:41 PM, "Dr Evelyn Hovenga" <ehovenga at> wrote:

> 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.
> Evelyn
> -----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.
> work-to-use-machines-for-health-analytics
> 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
> Bert
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