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Prevalences are forwarded to follow-up item directly from PPV screening items. With the context of "2000 woman participated..." the prevalence alone says things like "0.05% have breast cancer at the t…
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Add a question after PPV probability question about how willing is the person to undergo the screening test.
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In the pfab conditions we should show:
> Imagine a group of **prevalence_02_variable** women at age **age_variable** that go through a massive screening.
Should look:
> Imagine a group of **…
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Hi Wen tao,
I've read through your paper on deep MIL for mammogram mass classification and find there are three proposed method: 1) max-pooling based; 2) label assignment based and 3) sparse MIL
F…
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As far as I can tell, premeasures do not need to exist for Quality Measure 146 or 225. It will make data collection for these measures unnecessarily cumbersome. 146 is also confusing b/c it is pickin…
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Random forest example of usage can be found here.
[Link to resource](https://www.kaggle.com/jeffd23/scikit-learn-ml-from-start-to-finish)
Provide an example of usage for our problem if possible.
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Read the article [A New Local Adaptive Mass Detection Algorithm in Mammograms](https://github.com/OlehKSS/IMMAS/blob/master/Articles/A%20New%20Local%20Adaptive%20Mass%20Detection%20Algorithm%20in%20Ma…
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Some already have annotation information, but that needs to be improved.
Use https://canon-api.datausa.io/cubes as a template.
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This will be an additional Behavior variable with three values: "Poor Behavior", "Fair Behavior", "Good Behavior"
Poor Behavior
* No checkup, no mammogram or breast exam for females within the last …
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Now we have our segmentation method and true positive mask.
Should we calculate mass region features based on which segmentation, from our method or using ground truth result? Now we take features …