Machine Learning , some thoughts

Philippe Ameline philippe.ameline at
Mon Jun 25 08:47:07 EDT 2018

You may be interested in this paper (from my Tech Trends):

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.

Another point is that many medical documents don't get external feedback
and can be of very low quality. In France, patients leave the hospital
with an hospitalization report. My mother in law was admitted in an
hospital for 3 days several months ago, and her "outpatient report"
didn't mention any of the things she had discussed with doctors... and
her weight was supposed to be 20 kg less than her actual one.

Wrong patient, copy-pasted document not properly actuated?

Since nobody dare having this kind of document corrected, it remains
forever wrong in hospital's records. Successfully using machine learning
demands a prior culture of data quality and information awareness.



Le 25/06/2018 à 13:05, GF a écrit :
> 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 present.
> Most of that needed additional info can be obtained on the fly by
> IT-systems to be designed,
> Most of the context information (dates, times, locations, persons
> involved, relationships), are  available but never stored,
> Analysis of images, sounds, that might become feasible.
> Gerard   Freriks
> +31 620347088
>   gfrer at <mailto:gfrer at>
> Kattensingel  20
> 2801 CA Gouda
> the Netherlands
>> On 25 Jun 2018, at 12:52, Bert Verhees <bert.verhees at
>> <mailto:bert.verhees at>> wrote:
>> 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 designed, engineered and not hacked together.
>>> It is certain that AI applications in healthcare must be treated as
>>> Medical Devices.
>>> For it function properly we need to be able to document healthcare
>>> topics including the full context/epistemology.
>> I agree, especially on GP-level, I checked with my wife, she is GP,
>> as you (Gerard) know. I asked her if the context/epistemology in a
>> EHR is sufficient for machine-learning. It is not, she sufficient,
>> and that will never be. GP's have other things to do then carefully
>> record all datapoints that describe a disease.
>> Even when using archetyped-systems this does not change.
>> 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 has headache as a result
>> of fever and other inconveniences coming with infection disease.
>> So, the GP cannot do much with machine learning, the best source of
>> knowledge is his experience, and if he cannot solve with that, he
>> should ask someone else, or send the patient to the hospital to a
>> specialist.
>> But there, machine learning can do things in some specialties.
>> Anyway, thanks for your reply
>> Bert
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