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, or aspect of a person's healthcare and then a template describes a multidimensional "Point" which characterises the patient journey within the disease. Consider for example "Total Brain Volume". You can use it to track cognitive decline in AD (https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(04)15441-X/abstract) and this gives you one "explanatory variable". But, still, there are patients whose brain volume is abnormal (for their age) and they still perform well in other tests, so you need more "data points" (a richer template) around the phenomenon to understand it better. I think that what you are describing is something like "An automated approach to constructing disease specific 'Minimal Clinical Datasets'". 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. All the best Athanasios Anastasiou -----Original Message----- From: Bert Verhees <bert.verh...@rosa.nl> Sent: 25 June 2018 12:31 To: Anastasiou A. <a.anastas...@swansea.ac.uk>; For openEHR clinical discussions <openehr-clinical@lists.openehr.org> Subject: Re: Machine Learning , some thoughts 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 good enough for machine learning. I was too optimistic and to much impressed by some results of machine learning. It will do very good things in healthcare, but only on very specific cases. But while writing this What would be good, however, an improvement. I suggested to my wife (a GP), and she agreed (partly) Classic EHR software only has few datapoints on a screen, and many particularities come into free text, and if the GP is really motivated, maybe he finds some ICPC code. Archetypes do not really change this practice. A GP is a busy person. What could help is modularity. A GP should be able to add datapoints to his screen. For example, beside all the normal things, the GP sees that there are red eyes, but how can he make this available to the system in a way that it can be found back? 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 checkbox. Eventually a choice, A bit red, medium red, very red. This kind of software does not have to be something for the far future, but can be available already now. Also thanks to machine learning, a limited form of NLP (natural language expression (machine learning helping with NLP) can be used, and that was my idea of generating archetypes, last Saturday. A computer could, in some cases of simple datapoints, also even generate micro-archetypes for them, and with templates or container-archetypes, generate evaluation-archetypes Maybe, when it is so easy to create datapoints, and store them, maybe then machine learning in diagnostic can come closer, also in some cases for a GP, or machine learning can do suggestion: look to the tongue of the patient, but the fact remains, a good GP needs experience for diagnotics. Bert _______________________________________________ openEHR-clinical mailing list openEHR-clinical@lists.openehr.org http://lists.openehr.org/mailman/listinfo/openehr-clinical_lists.openehr.org
