On 03-07-18 13:13, Anastasiou A. wrote:
Initially, I thought that it would have been this one
Opinions from yesterday may still be valid today.
Inventions and business models follow up quickly. But the law is behind,
as law should be: conservative, keeping an eye on human rights.
On 03-07-18 12:21, Philippe Ameline wrote:
Le 02/07/2018 à 11:31, Bert Verhees a écrit :
On 30-06-18 17:16, Philippe Ameline wrote:
(improperly labeling images or adding images of objects that are not
plants) could probably make the whole app plainly crappy.
Of course Philippe, but that
BTW, is someone aware of this project by Google?
https://ai.googleblog.com/2018/05/deep-learning-for-electronic-health.html
Le 03/07/2018 à 12:40, Birger Haarbrandt a écrit :
> Hi Philippe,
>
> I completely agree with your view. This is why data stewardship is
> needed before we can make real
Hi Philippe,
I completely agree with your view. This is why data stewardship is
needed before we can make real use of the data:
https://en.wikipedia.org/wiki/Data_steward
As we use this approach in HiGHmed, I might be able to report in 2020
about lessons learned :)
Best,
--
*Birger
Le 02/07/2018 à 11:31, Bert Verhees a écrit :
> On 30-06-18 17:16, Philippe Ameline wrote:
>> (improperly labeling images or adding images of objects that are not
>> plants) could probably make the whole app plainly crappy.
>
> Of course Philippe, but that would be vandalism. Most sensible people
On 30-06-18 17:16, Philippe Ameline wrote:
(improperly labeling images or adding images of objects that are not
plants) could probably make the whole app plainly crappy.
Of course Philippe, but that would be vandalism. Most sensible people
don't do that when they stand behind the goal, and a
Data of perfect quality means, in my opinion, data and their complete context.
A diagnosis by a nurse is not the same as one by a patiente, or strting intern,
or one MD with 20m years experience.
Just mentioning one example.
Gerard Freriks
+31 620347088
gf...@luna.nl
Kattensingel 20
2801
Le 27/06/2018 à 22:26, Bert Verhees a écrit :
> On 27-06-18 16:43, Philippe Ameline wrote:
>> 1) you can find a bunch of practitioners that agree on working extra
>> hours to comment a big bunch of images, or
>
> Did I tell you about the plant-app? I believe I did. 700.000 pictures
> are
On 29-06-18 10:26, Thomas Beale wrote:
I think you have a good point about the documented uses of archetypes
potentially being too narrow - it would be worth a global review to
see if anything already there can be used for purposes different from
that originally envisaged. I wonder if
On 29-06-18 07:38, Heather Leslie wrote:
BTW Bert - here's a project that has some archetypes that might be useful for
your diet app scenario:https://ckm.openehr.org/ckm/#showProject_1013.30.47.
They were volunteered by some of our Portuguese colleagues and refined by CKM
Editors.
Thanks, I
On 29-06-18 07:13, Heather Leslie wrote:
please try not to disseminate this kind of message.
I understand the message, Heather, and every time when I express some
criticism about how CKM is functioning, I never forget to tell how
important it is and how good work it is. When you would had
On 29-06-18 01:11, GF wrote:
Any one automobile or airplane or house is built using many, many
standards.
You are right Gerard, that was I was in my joke explicitly talking about
interoperability standards.
Bert
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Exactly right. Archetypes are high-value clinical informatics work, and
they are free. Making more of them, faster, means getting more clinician
and informatician time, which means that projects who would like to have
domain models of information and process - even if their final
consumption
AM
*To:* For openEHR clinical discussions
; Bert Verhees
*Subject:* Re: Machine Learning , some thoughts
One other example of "a big bunch of" things is https://www.snomed.org/.
This does not come for free. Snomed works along a well defined set of
processes, performed by experts w
On Thu, Jun 28, 2018 at 08:34:20AM +0200, GF wrote:
> The GDPR allows the collection of health data.
> The GDPR restricts itself to person identifiable data and it secondary
> use/abuse of privacy rights.
>
> Since health and care are about all of society, all of life, all must be able
> to be
On 28/06/2018 15:49, Bert Verhees wrote:
That could be possible, but then you get structure, and
node-identifiers. Maybe just flat paths are more convenient, so that
the OBSERVATION archetypes do not require CLUSTERS but ITEMs so that
it is possible to include ELEMENTs on that point. I
M
> To: Bert Verhees
> Cc: For openEHR clinical discussions
> Subject: Re: Machine Learning , some thoughts
>
> Bert,
>
> Any one automobile or airplane or house is built using many, many standards.
>
> The models/standards I mentioned deal with a particular aspect o
-Original Message-
> From: openEHR-clinical On
> Behalf Of Thomas Beale
> Sent: Friday, 29 June 2018 12:13 AM
> To: openehr-clinical@lists.openehr.org
> Subject: Re: Machine Learning , some thoughts
>
>
>
> On 27/06/2018 16:57, Bert Verhees wrote:
> >
>
Of Thomas Beale
Sent: Friday, 29 June 2018 12:13 AM
To: openehr-clinical@lists.openehr.org
Subject: Re: Machine Learning , some thoughts
On 27/06/2018 16:57, Bert Verhees wrote:
>
> I have sport-app which tells me the power I produce, and it tells me
> that in Watt/kg That is more
about openEHR.
Regards
Heather
From: openEHR-clinical On Behalf
Of Bert Verhees
Sent: Wednesday, 27 June 2018 10:00 PM
To: openehr-clinical@lists.openehr.org
Subject: Re: Machine Learning , some thoughts
Dear Seref, I do not agree with this without having explored all the
possibilities. I
to take action through
the relevant organisations.
Evelyn
From: openEHR-clinical On Behalf
Of GF
Sent: Friday, 29 June 2018 9:12 AM
To: Bert Verhees
Cc: For openEHR clinical discussions
Subject: Re: Machine Learning , some thoughts
Bert,
Any one automobile or airplane or house
Bert,
Any one automobile or airplane or house is built using many, many standards.
The models/standards I mentioned deal with a particular aspect of data to be
stored, retrieved, processed and exchanged.
Data that is generated in and by a patient in a context,
observed by a person in a context
available at
https://www.thieme-connect.de/products/ejournals/pdf/10.15265/IY-2016-015.pdf
provides an overview of its mission and membership.
Evelyn
From: openEHR-clinical On Behalf
Of GF
Sent: Friday, 29 June 2018 7:50 AM
To: For openEHR clinical discussions
Subject: Re: Machine Learning
Gerard Freriks
+31 620347088
gf...@luna.nl
Kattensingel 20
2801 CA Gouda
the Netherlands
> On 28 Jun 2018, at 16:03, Stefan Sauermann
> wrote:
>
> Instead, the greatest hope for effective systems will be realized when the
> infrastructure for introducing computational tools in
Evelyn
From: openEHR-clinical On Behalf
Of Stefan Sauermann
Sent: Friday, 29 June 2018 12:04 AM
To: For openEHR clinical discussions ; Bert
Verhees
Subject: Re: Machine Learning , some thoughts
One other example of "a big bunch of" things is https://www.snomed.org/.
This d
Hmm... imagining...
Steps walked | phone in trouser pocket
| phone in handbag | strap length
:-)
Colin
> On 27 Jun 2018, at 6:13 pm, Anastasiou A. wrote:
>
> Imagine Steps_Walked defined separately for FitBit, FitBlit, FitZit, FitBic,
> etc,
> I agree there is a need to be able to create archetypes much more
quickly based on device specifications. We need to work on that.
If you are looking for device specifications, I guess you are aware of
the medical device information model and the nomenclature of ISO EN IEEE
11073?
On 28-06-18 10:33, Thomas Beale wrote:
On 27/06/2018 13:00, Bert Verhees wrote:
Dear Seref, I do not agree with this without having explored all the
possibilities. I think it is important not to jump to conclusions and
keep the discussion open.
I have some ideas how to keep it interoperable.
On 28-06-18 16:12, Thomas Beale wrote:
On 27/06/2018 16:57, Bert Verhees wrote:
I have sport-app which tells me the power I produce, and it tells me
that in Watt/kg
That is more important then BMI, because athletes can have a BMI
above thirty (muscles are heavier then fat) and be very
On 27/06/2018 16:57, Bert Verhees wrote:
I have sport-app which tells me the power I produce, and it tells me
that in Watt/kg
That is more important then BMI, because athletes can have a BMI above
thirty (muscles are heavier then fat) and be very healthy, so
important is to know what they
Correct! That is what I meant.
If clinicians decide that something must be documented, they do so in
fulfilment of the "doctors" law (at least in Austria). The GDPR is
therefore satisfied (as far as I understand).
Stefan
Am 27.06.2018 um 12:48 schrieb Diego Boscá:
I assume that when Stefan
> I don't know who May is but
May is many ;-)
Sorry, no time now, later I come back to your message
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The discussion between Stefan and Karsten is about data related to an
identifiable person, so gdpr is applicable.
I hope I resume it right:
Karsten says that it is illegal to collect data about a person if the
purpose id not known. This is because Stefan says that it is allright to
collect data
> Maybe it is not really generated but delivered by the producer of the
> device, a minimalistic archetype, it is not important, important is that
> it a minimalistic archetype is which can contain the data which are to
> delivered.
> Most manufacturers will not write
When it necessary and defendable data can be collected and used.
Explicitly kinds of data and organisations are mentioned that can store more
data than most others.
Healthcare and political parties are examples special catagories.
Clause 53 deals with health and care
Gerard
Dear Karsten,
The GDPR allows the collection of health data.
The GDPR restricts itself to person identifiable data and it secondary
use/abuse of privacy rights.
Since health and care are about all of society, all of life, all must be able
to be documented.
No restrictions.
So I disagree with:
On 27-06-18 16:43, Philippe Ameline wrote:
1) you can find a bunch of practitioners that agree on working extra
hours to comment a big bunch of images, or
Did I tell you about the plant-app? I believe I did. 700.000 pictures
are reviewed, often by volunteers.
The app recognizes 16000
On 27-06-18 18:55, Anastasiou A. wrote:
openEHR goes back to 1994 and its ideas are starting to become more widely
known in the last few years.
It is true, especially thanks to the good work of Marand but also others.
As long as it is not part of medical school training, I do not think the
>>> Semantics is also something in the eye of the beholder.
>> That's what I would be worried about.
>> If that company's archetypes were not derived by the bigger conceptual
>> model, it would only make sense to its ecosystem.
> You can always map them to structures FHIR requires, and that is
On 27-06-18 17:12, Anastasiou A. wrote:
A few notes:
You cannot specialise the Blood Pressure Archetype to express anything other
than blood pressure as far as I am aware.
I am not sure about that, but it is not important in how I think about it.
Because the micro-archetypes contain valid
A few notes:
>>You cannot specialise the Blood Pressure Archetype to express anything other
>>than blood pressure as far as I am aware.
> I am not sure about that, but it is not important in how I think about it.
> Because the micro-archetypes contain valid paths, they can be queried.
> A
Bert, I don't think that we really disagree there. As you nail it the
dataset comes from people agreeing on building it the proper way. And
agreeing with Karsten (who is plainly right), doesn't make that process
simple.
Means that wether:
1) you can find a bunch of practitioners that agree on
On 27-06-18 15:14, Anastasiou A. wrote:
Not as “fact”, it is probably how I expressed it, this is my
understanding so far and I would not mind it being corrected if wrong.
>It is an archetype, it is written in ADL following the ADL-syntax, it
is processable by AOM, it consists of datatypes
Dear Bert,
Always happy to keep a discussion open and I appreciate your input. I'm
sure achieving the kind of agility without introducing the problems I
mentioned would be of interest to many people, so by all means feel free to
make suggestions.
The market is a commercial dynamic. It is true
From: openEHR-clinical On Behalf
Of Bert Verhees
Sent: 27 June 2018 13:52
To: openehr-clinical@lists.openehr.org
Subject: Re: Machine Learning , some thoughts
Thanks for your reply, Anastasiou,
I disagree with some opinions you express as fact.
On 27-06-18 14:21, Anastasiou A.
Thanks for your reply, Anastasiou,
I disagree with some opinions you express as fact.
On 27-06-18 14:21, Anastasiou A. wrote:
I think that this is the bit that causes the “friction” J
“Archetype” is not a “value”. It is a type.
It is an archetype, it is written in ADL following the
>The same things you have to do when you need to handle a generated archetype.
>But it will not be that hard. Don't expect much complexity from these
>generated archetypes.
>I called them before, micro-archetypes, containing only one datapoint, or a
>few closely related datapoints.
>With
Dear Seref, I do not agree with this without having explored all the
possibilities. I think it is important not to jump to conclusions and
keep the discussion open.
I have some ideas how to keep it interoperable. I like to discuss that
with an open mindset.
Talking about interoperability.
By
On Wed, Jun 27, 2018 at 12:48:11PM +0200, Diego Boscá wrote:
> I assume that when Stefan says "all", he is referring to these extra data
> points, which can be identified and accepted (or not), even on a one-by-one
> basis if needed
That would, formally, fulfil the requirements :-)
Which, of
I assume that when Stefan says "all", he is referring to these extra data
points, which can be identified and accepted (or not), even on a one-by-one
basis if needed
2018-06-27 12:36 GMT+02:00 Karsten Hilbert :
> On Wed, Jun 27, 2018 at 12:28:30PM +0200, Diego Boscá wrote:
>
> > Technically it's
On Wed, Jun 27, 2018 at 12:28:30PM +0200, Diego Boscá wrote:
> Technically it's ok if patients/citizens are aware of it (and willing to
> share it)
No, because the basic rule is that
everything is forbidden
except where
explicitely allowed
PLUS
Technically it's ok if patients/citizens are aware of it (and willing to
share it)
2018-06-27 12:18 GMT+02:00 Karsten Hilbert :
> On Wed, Jun 27, 2018 at 11:57:05AM +0200, Stefan Sauermann wrote:
>
> > I agree completely that it is not possible to know which information is
> > relevant, and that
I don't think this completely breaks openEHR. Even Thomas talks about how
many "data points" there are in the CKM right now. Probably we could
(re)use each one of these data points on their own, keeping their meaning.&
creating/reviewing them by using a modeling methodology.
2018-06-27 11:50
On Wed, Jun 27, 2018 at 11:57:05AM +0200, Stefan Sauermann wrote:
> I agree completely that it is not possible to know which information is
> relevant, and that all information is better recorded just in case
Not that I like the fact but that is currently illegal under EU GDPR.
Karsten
--
GPG
One short addition, why this discussion, the original point:
What about machine learning?
Machine learning becomes possible when many daily health related data are
available. A machine can, f.e. detect deviations.
Why generated archetypes?
Every day there are new devices, new ideas about health,
Thanks for supporting reactions.
It is really typical in western medical science that it is very problem
oriented. All EHRs, even unconventional one, even the new thinking, it is
very problem oriented.
All data are gathered around a problem and in relevance of a problem. All
datastructures are
> To: Stefan Sauermann ; For openEHR clinical
> discussions
> 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 cle
> 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
Dear Bert,
You mention:
"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."
If there is some semantics: The archetype to store this information will then
need at least some structure, and not
; Evelyn
>
> -Original Message-
> From: openEHR-clinical On
> Behalf Of Bert Verhees
> Sent: Wednesday, 27 June 2018 12:17 AM
> To: Stefan Sauermann ; For openEHR clinical
> discussions
> Subject: Re: Machine Learning , some thoughts
>
> On 26-06
discussions
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 re
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
> Therefore I conclude for myself that I will not trust (and recommend to
> trust) automatically found archetypes, because you can not derive
> reliable conclusions from them at a defined level of reliability.
Stefan, I give a short reply, I have already given much input in this
discussion and
One needs patters that document the documentation process in general for
Medical Statements, Evaluations, Orders, Actions
Patterns to Collect Complaints
Patterns to Collect Observations by tractus
Patterns to collect complaint specific data
Patterns to collect Diagnosis specific data
Patterns to
Verhees
Sent: 25 June 2018 14:35
To: Anastasiou A. ; For openEHR clinical discussions
Subject: Re: Machine Learning , some thoughts
On 25-06-18 14:56, Anastasiou A. wrote:
Once you have this minimal dataset discovered, THEN you could compose the
template or automatically create the archetypes
stasiou
>
>
>
>
>
>
> -Original Message-
> From: Bert Verhees
> Sent: 25 June 2018 12:31
> To: Anastasiou A. ; For openEHR clinical
> discussions
> Subject: Re: Machine Learning , some thoughts
>
> On 25-06-18 12:44, Anastasiou A. wrote:
hat would
enable all this. Maybe things are progressing faster where you are (?)
All the best
Athanasios Anastasiou
-Original Message-
From: Bert Verhees
Sent: 25 June 2018 14:35
To: Anastasiou A. ; For openEHR clinical
discussions
Subject: Re: Machine Learning , some thoughts
On 25-
Excellent observations!!!
Carol
El 25-06-2018, a las 07:30, Bert Verhees escribió:
On 25-06-18 12:44, Anastasiou A. wrote:
The time scales for doing this would be enormous. We can probably work out a
lower limit by looking at the lifecycle of archetypes
in the current CKM.
Thanks, for your
On 25-06-18 14:56, Anastasiou A. wrote:
Once you have this minimal dataset discovered, THEN you could compose the
template or automatically create the archetypes.
And yes, this CAN be done today, definitely.
There is an understandable mindset which aspires to work with a
standard-set of
On 25-06-18 14:47, Philippe Ameline wrote:
Successfully using machine learning demands a prior culture of data
quality and information awareness.
Dear Philippe, I read your document later.
I have to disagree with the word "prior".
It makes it sound like, is has gone wrong long time ago, and
On Mon, Jun 25, 2018 at 02:47:07PM +0200, Philippe Ameline wrote:
> A friend of mine recently published a paper, after studying a group of
> GPs located in the South of France. He found out that the diagnosis is
> not reported in observations in more than one encounter out of two.
That's because
compose the
template or automatically create the archetypes.
And yes, this CAN be done today, definitely.
All the best
Athanasios Anastasiou
-Original Message-
From: Bert Verhees
Sent: 25 June 2018 12:31
To: Anastasiou A. ; For openEHR clinical
discussions
Subject: Re: Machine Lea
d number. We can also use archetypes
> we do not know, and maybe we never know. Even, we wouldn't need archetypes
> anymore, just as reminder/instruction. But the computer could create the
> archetypes on the fly, when seeing the kind of data, the relations, the
> diagnosis.
>
> 2) We could use
On 25-06-18 12:44, Anastasiou A. wrote:
The time scales for doing this would be enormous. We can probably work out a
lower limit by looking at the lifecycle of archetypes
in the current CKM.
Thanks, for your answer, I agree with you and others, and already wrote
that, that an EHR will not be
Largely I agree with Bert.
Medicine is an art for 80% and science for 20%
What medical data is recorded in most cases by GP’s is so scanty that AI is not
possible.
Collecting data over long periods of time might help.
Most IT-systems can not store all the epistemology that is needed for AI, at
On 25-06-18 12:31, Thomas Beale wrote:
On 25/06/2018 11:21, Stefan Sauermann wrote:
82% of correct recognition rate is a desaster in healthcare.
92% would be a disaster in healthcare ...
74% is even worse.
My evidence based feeling is that we still will need to sort it out
manually for
On Mon, Jun 25, 2018 at 12:52:07PM +0200, Bert Verhees wrote:
> Allthough, there are some patient-conditions which are very typical for a
> disease, mostly this is not the case.
> For example, many infection-diseases have fever as a symptom, and one person
> gets pain in his back, and the other
On 25-06-18 12:21, Stefan Sauermann wrote:
Hope this helps,
Not really Stefan, but thanks for trying.
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On 25-06-18 12:40, GF wrote:
Providing health and care is part science and for a large part an art.
Meaning that humans are needed.
Artificial Intelligence is a nice scientific hyped topic and nothing more.
That is not to say that AI might play a role and can be of use.
It needs to be properly
On Mon, Jun 25, 2018 at 11:31:27AM +0100, Thomas Beale wrote:
> > 82% of correct recognition rate is a desaster in healthcare.
>
> 92% would be a disaster in healthcare ...
It much depends. In typical care "92%" (of what ?) can be an
extremely brilliant result far beyond anything available
Dear Bert and all
> I wonder, Is OpenEhr usable for recognizing pattern in diseases over
> Machine Learning, isn't behind every diagnosis a small cloud of
> archetypes which forms a pattern? The features of recognizing/learning
> should not be found in archetypes ID's, although, that can help
s is developed, we should be able to get to at least two
>> advantages.
>>
>> 1) We don't need CKM anymore, computers can understand archetypes, we don't
>> need to restrict ourselves to a limited number. We can also use archetypes
>> we do not know, and mayb
On Mon, Jun 25, 2018 at 12:21:26PM +0200, Stefan Sauermann wrote:
> My evidence based feeling is that we still will need to sort it out manually
> for some years to come.
Not in visual classification of dermatological health concerns.
Or areas of radiological diagnostics.
Karsten Hilbert
--
On 25/06/2018 11:21, Stefan Sauermann wrote:
82% of correct recognition rate is a desaster in healthcare.
92% would be a disaster in healthcare ...
74% is even worse.
My evidence based feeling is that we still will need to sort it out
manually for some years to come.
I am slightly more
he kind
of data, the relations, the diagnosis.
2) We could use the pattern to recognize healthcare situations, and
maybe treat/handle/cure on base of instructions coming from machine
learning.
Some thoughts when walking with my wife through the wonderful dunes,
and its special vegetation.
of instructions coming from machine
learning.
Some thoughts when walking with my wife through the wonderful dunes, and
its special vegetation. Maybe I must write a blog about it.
Have a nice day.
Bert
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