Publications by authors named "H Peter Smits"

Chronic pain is an ill-defined disease with complex biopsychosocial aspects, posing treatment challenges. We hypothesized that treatment failure results, at least partly, from limited understanding of diverse patient subgroups. We aimed to identify subgroups using psychological variables, allowing for more tailored interventions.

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The proximity extension assay (PEA) enables large-scale proteomic investigations across numerous proteins and samples. However, discrepancies between measurements, known as batch-effects, potentially skew downstream statistical analyses and increase the risks of false discoveries. While implementing bridging controls (BCs) on each plate has been proposed to mitigate these effects, a clear method for utilizing this strategy remains elusive.

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Purpose: Deep learning is a promising approach to increase reproducibility and time-efficiency of gross tumor volume (GTV) delineation in head and neck cancer, but model evaluation primarily relies on manual GTV delineations as reference annotation, which are subjective and tend to overestimate tumor volume. This study aimed to validate a deep learning model for laryngeal and hypopharyngeal GTV segmentation with pathology and to compare its performance with clinicians' manual delineations.

Methods And Materials: A retrospective data set of 193 patients with laryngeal and hypopharyngeal cancer was used to train a deep learning model with clinical GTV delineations as reference.

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Background: SARS-CoV-2 has been associated with a higher proportion of asymptomatic infections and lower mortality in sub-Saharan Africa than high-income countries. However, there is currently a lack of data on cellular immune responses to SARS-CoV-2 in people living in Africa compared with people in high-income regions of the world. We aimed to assess geographical variation in peripheral and mucosal immune responses.

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