Publications by authors named "A Ultsch"
Article Synopsis
- Small sample sizes in biomedical research lead to poor reproducibility and difficulties in applying findings clinically, caused by factors like limited resources and ethical concerns.
- A new generative algorithm leveraging self-organizing maps (SOMs) has been developed to effectively increase sample sizes by identifying structures in small datasets and generating new data points without altering the original data's integrity.
- Experiments show that the generated data maintains the same structure as the original, aiding research in rare diseases like leukemia and arthritis, and the method is available through the R library "Umatrix."
Fold change is a common metric in biomedical research for quantifying group differences in omics variables. However, inconsistent calculation methods and inadequate reporting lead to discrepancies in results. This study evaluated various fold-change calculation methods aiming at a recommendation of a preferred approach.
View Article and Find Full Text PDFPsoriatic arthritis (PsA) is a chronic inflammatory systemic disease whose activity is often assessed using the Disease Activity Score 28 (DAS28-CRP). The present study was designed to investigate the significance of individual components within the score for PsA activity. A cohort of 80 PsA patients (44 women and 36 men, aged 56.
View Article and Find Full Text PDFRandom walks describe stochastic processes characterized by a sequence of unpredictable changes in a random variable with no correlation to past changes. This report describes the random walk component of a clinical sensory test of olfactory performance. The precise definition of this stochastic process allows the establishment of precise diagnostic cut-offs for the identification of olfactory loss.
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