Many Machine learning applications are analogous to "experience'
ie pattern recognition
Typical ML algorithms require training data where the results are
known . They seem to have most application in areas where there are
massive amounts of data which a human cannot comprehend -
> 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 wan
Pattern recognition could be done with AI systems using a large selection of
health records, to suggest new, possibly unexpected archetypes, but not yet.
As commented earlier, data are not sufficiently recorded yet, specialists are
too busy; responsibilities are left undefined as patients move f
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
On 25-06-18 16:51, Anastasiou A. wrote:
Hello Bert and all
I wonder if besides that approach an approach of archetypes growing in the wild
could be of use. They could be used beside the predefined archetypes.
I don't think that enabling people to create local fragmented subsets of
informatio
It is a truth that, in the case of GP’s, almost always they deal with
Complaints, Tentative diagnosis or estimation of the Seriousness (good/bad
feeling), some trial Therapies and some addition investigations/tests, plus
finally some time to observe the evolution of the complaints over time; aw
Hello Bert and all
> I wonder if besides that approach an approach of archetypes growing in the
> wild could be of use. They could be used beside the predefined archetypes.
I don't think that enabling people to create local fragmented subsets of
information is a step in the right direction. We
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 an
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 arch
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 t
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
Hello Bert and all
I am a little bit "worried" with "micro-archetypes" the way you describe them.
I think that what you are probably referring to is "Disease Specific
Templates", which I really hope is what we are all working towards :)
So, archetypes do indeed describe one conceptual quantity
Have anyone tried AQL adapter to pandas(python data analysis package
for machine learning and statistics)?
Shinji
2018-06-24 1:11 GMT+09:00 Bert Verhees :
> Today my wife showed me Plantnet.
>
> https://plantnet.org/en/
>
> It recognizes over 6000 plants from showing a flower or a leaf to your
>
You may be interested in this paper (from my Tech Trends):
http://philippe.ameline.free.fr/techtreads/additionalMaterial/Boyd_MagicOfBigDataAndArtificialIntelligence.pdf
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
On 25-06-18 13:52, Karsten Hilbert wrote:
This approach much reminds me of what Philippe (sp?)
described of his fils guides. Instances of "micro achetypes"
would be generated on the fly while typing/speaking.
The doctor mumbles to his screen while the patient tells it story, or
the doctor does
On Mon, Jun 25, 2018 at 01:30:30PM +0200, Bert Verhees wrote:
> What about micro-archetypes which describe only one datapoint? And the GP
> should be able to invoke them by voice. He says "red eyes" and magic
> happens, there is a datapoint on the screen which offers a possibility to
> click on a
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 ha
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
today
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 a
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 designed, engineered and not ha
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
--
GP
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
82% of correct recognition rate is a desaster 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.
Hope this helps,
Stefan
Stefan Sauermann
Program Director
Biomedical Engineering Sciences (Master) ->
Medical E
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