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@@ -58,3 +58,32 @@ I'm considering making this open source. If you'd like to contribute please give
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  [^1] Duke Study https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2783046
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  [^2] [cancerimagingarchive https://www.breastcancer.org/facts-statistics](https://www.cancerimagingarchive.net/collection/breast-cancer-screening-dbt)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  [^1] Duke Study https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2783046
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  [^2] [cancerimagingarchive https://www.breastcancer.org/facts-statistics](https://www.cancerimagingarchive.net/collection/breast-cancer-screening-dbt)
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+ A study conducted by Duke University Health System assessed "deep learning" and "medical imaging in general" have significant advancements left to go in the future.
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+ Their conclusion comes following thier own AI models, trained to detect cancer in a non-invasive way(requiring no biopsy), was evaluated at only 65% sensitivity.
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+ Although in reality no easy feat, a disappointing statistic from the US's 7th best University.
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+ I, having experience in the industry & seeking a meaningful project to work on, felt compelled to see what I could do to move the needle.
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+ The result of this was creating a model which was evaluated at 62% using scikit-learn's classification report.
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+ The model is hosted on Hugging Face linked below. And soon radiologist & patients will all be able to use this model for free(and future improved versions of it) at https://lnkd.in/eTWCD2wu
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+ https://lnkd.in/eTx_sw9k