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thenineteen / Semiology-Visualisation-Tool

Data driven 3D brain visualisation of semiology. Semiology to anatomy translator based on over 4600 patients from 309 peer-reviewed articles.
MIT License
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How to combine semiologies #2 #221

Closed thenineteen closed 3 years ago

thenineteen commented 3 years ago

original issue on combining semiologies #8 used MinMaxScaler and softmax. MinMaxScaler is sensitive to range and doesn't account for variance. Softmax is only great for the top prediction.

After proportions were supported akin to probabilities #118, we can now combine semiologies in a statistically more sound manner by using proportions and inverse variance weighting as alluded to in #8

thenineteen commented 3 years ago

in branch Bayesian-correction pull #222 this allows inverse variance weighting by modelling the GIF parcellations as binomial random variables (and the marginals p(semiology) from SS and p(GIF) from TS data), as well as an equal weightings (mean) method.

variance of binomial proportions = p(1-p)/n

I discussed these methods with Chibueze, Tim Stone, Normal WIliams from UCL, and they all agreed should prefer the above (cf both marginals from all-data, or using the data-query results as the estimate of the marginals).

NB this is an approximation as the GIFs are not independent (e.g.if it involves amygdala, likely will involve hippocampus)