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Most machine learning-based computer-aided diagnosis approaches have been designed and validated using research data sets. It is thus not clear how they would generalise to clinical routine and ultimately what is their medical value.
We are currently exploiting real-life data from hospital data warehouses (specifically the data warehouse of the 39 Greater Paris hospitals - AP-HP, comprising millions of patients) to perform such evaluation. This talk will present the challenges we have to deal with related to the quality and heterogeneity of the imaging data. It will also highlight the solutions we have proposed.
Ninon Burgos
"Exploiting hospital data warehouses: the challenges of image quality and heterogeneity (Conference Presentation)", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124640N (3 April 2023); https://doi.org/10.1117/12.2672591
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Ninon Burgos, "Exploiting hospital data warehouses: the challenges of image quality and heterogeneity (Conference Presentation)," Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124640N (3 April 2023); https://doi.org/10.1117/12.2672591