Publications by authors named "B C Moor"

Background: Modern machine learning and deep learning methods have been widely incorporated in decision making processes in healthcare in the form of decision support mechanisms. In healthcare, data are abundant but typically not centrally available and, therefore, require some form of aggregation to facilitate training procedures. Aggregating sensitive data poses a significant privacy risk, which is why, both in Europe and the United States, legal frameworks regulate the treatment of such data.

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The role of immunosuppressive therapy on SARS-CoV-2 infection risk and COVID-19 severity remains unclear in unvaccinated solid organ transplant recipients. We included 1957 organ transplant recipients between July 2020 and April 2021 to analyze whether baseline immunosuppressive therapy and other risk factors are associated with SARS-CoV-2 infection and severe COVID-19. In total, 247 (12.

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One of the main challenges in mass spectrometry imaging data analysis remains the analysis of /-spectra displaying a low signal-to-noise ratio caused by their low abundance, sample preparation, matrix effects, fragmentation, and other artifacts. Additionally, we observe that molecules with a high abundance suppress those with lower intensities and misdirect classical tools for MSI data analysis, such as principal component analysis. As a result, the observed significance of a molecule may not always be directly related to its abundance.

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Imaging mass spectrometry (IMS) provides promising avenues to augment histopathological investigation with rich spatio-molecular information. We have previously developed a classification model to differentiate melanoma from nevi lesions based on IMS protein data, a task that is challenging solely by histopathologic evaluation. Most IMS-focused studies collect microscopy in tandem with IMS data, but this microscopy data is generally omitted in downstream data analysis.

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