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Label normalization experiment (label loss and ailment simplification)

Upcoming label normalization experiment:

Dear followers, you may remember my label normalization function post recently that would take a set of given labels and their symptoms, remove the labels and any duplicate symptoms and only leave the remaining essence of the patients problem (assumed) in the form of the remaining symptoms. I appreciate feedback on my efforts to support and verify whether my work is accurate and so am open to suggestions from the observations of others.

This post is to inform my followers that there will be an upcoming major label normalization experiment with a large amount of disorders in the DSM. This will be done to demonstrate the power of the label normalization engine and the benefits in the use of database science and psychiatry combined. It is unsure whether this experiment will be successful however with trial and error it is my goal to develop an engine that effectively allows a patient to lose their labels and the redundant additional baggage that comes with labels such as duplicate symptoms in a multi diagnoses. I am seeing signs already of what I personally believe to be progress towards label loss which has sparked my curiosity to further develop this engine.

I intend on making this function available globally for free.

Below is an update of the Simplifier (normalize) function with more labels added. I am currently trying to add as many labels as I can for the experiment and also get the associated symptoms.