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A study of why we need to reassess full reference image quality assessment with medical images
Image quality assessment (IQA) is not just indispensable in clinical practice to ensure high standards, but also in the development stage of novel algorithms that operate on medical images with reference data.
Navigating the challenges in creating complex data systems: a development philosophy
In this perspective, we argue that despite the democratization of powerful tools for data science and machine learning over the last decade, developing the code for a trustworthy and effective data science system (DSS) is getting harder.
Classification of datasets with imputed missing values: does imputation quality matter?
Classifying samples in incomplete datasets is a common aim for machine learning practitioners, but is non-trivial.
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