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In the initial system, a new problem case is constructed when the new patient arrives.
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In CBR, in order to solve a new problem, cases with features that are most similar to the new problem are retrieved from a case library, and their solutions are considered for reuse.
President Theodore Roosevelt issued an edict in 1906 that gave the Government Printing Office a list of 300 words with new spellings: problem cases like artisan, kissed and woe were to be changed to artizan, kist and wo.
ML-CBP is a case-based approach that leverages the incomplete model and the plan cases to solve a new problem directly by affecting case-level transfer.
In a kind of "reflective adjustment", they fit the new problem into a patchwork of past case decisions, comparing cases in order to reason about the legal significance of the relevant similarities and differences.
CBR is a knowledge paradigm that solves a new problem by finding the old similar cases and reusing them.
The HYPO family of systems implements a "lazy" approach since they defer making arguments how to decide a problem until the programs have positioned a new problem with respect to similar past cases.
However existing cases must be adapted to new problem situation.
A new problem exists.
Then a new problem arose.
In many cases, physical or biological causes of mental problems need to be ruled out first if this is a new problem.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com