Machine Learning , some thoughts

Shinji KOBAYASHI skoba at
Mon Jun 25 08:53:34 EDT 2018

Have anyone tried AQL adapter to pandas(python data analysis package
for machine learning and statistics)?


2018-06-24 1:11 GMT+09:00 Bert Verhees <bert.verhees at>:
> Today my wife showed me Plantnet.
> It recognizes over 6000 plants from showing a flower or a leaf to your
> phone. It has learned from machine-learning 700.000 pictures, and its
> knowledge every day grows stronger, because it keeps on learning. And not
> only the looks of a flower, but if it takes location (biotope) and date in
> consideration, the certainty of recognizing gets stronger.
> Now you can imagine that it must be hard to recognize a plant from a
> picture, without seeing the dimensions and showed in many possible angles,
> in sunlight, cloudy or twilight.
> I was impressed how good it already was. Very advanced computer-knowledge
> for free in the hands of the millions.
> There is also an app, I did not try it, which recognizes birds from audio.
> You walk somewhere, hear a bird and want to know what kind of bird that is.
> The Berlin Natural History Museum leads a contest of 29 teams using 23
> different methods, with more than 82% good identifications for isolated bird
> recordings, and more than 74% correct identifications for recordings mixing
> several bird songs.
> I often notice there is a trend in thinking that Machine Learning cannot be
> much help, see how miserable google-translate translates. But then we for
> get to see how much progress is made in other areas.
> Why am I writing this? Just to let you think about it.
> 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 lot, but it should also look to
> datatypes, their semantics and relations.
> Isn't OpenEhr better for recognizing pattern then whichever classic storage
> structure, because the data-structures in OpenEhr are in semantic models,
> this instead of some weird Codd-structure, which only has technical reasons
> to exist.
> (Classic data stored in classic SQL schema's could be brought over to
> archetyped structures, to make the base of machine-learning larger.)
> I think, when this 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 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 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. Maybe I must write a blog about it.
> Have a nice day.
> Bert
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