338 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of SalzburgAT5 papers
- Technical University of MunichDE3 papers
- University of KentuckyUS3 papers
- Christian Doppler KlinikAT2 papers
- Heidelberg UniversityDE2 papers
- Johannes Kepler University of LinzAT2 papers
- Ludwig-Maximilians-Universität MünchenDE2 papers
- University Hospital CologneDE2 papers
- University of CologneDE2 papers
- Acibadem City ClinicBG1 paper
- AIT Austrian Institute of Technology GmbHAT1 paper
- Al-Azhar UniversityEG1 paper
11 papers
Histo-Miner: Deep learning based tissue features extraction pipeline from H&E whole slide images of cutaneous squamous cell carcinoma
Lucas Sancéré, Carina Lorenz, Doris Helbig +9
Recent advancements in digital pathology have enabled comprehensive analysis of Whole-Slide Images (WSI) from tissue samples, leveraging high-resolution microscopy and computationa…
The Last JITAI? Exploring Large Language Models for Issuing Just-in-Time Adaptive Interventions: Fostering Physical Activity in a Conceptual Cardiac Rehabilitation Setting
David Haag, Devender Kumar, Sebastian Gruber +7
We evaluated the viability of using Large Language Models (LLMs) to trigger and personalize content in Just-in-Time Adaptive Interventions (JITAIs) in digital health. As an interac…
Shorter duration of slow wave sleep is related to symptoms of depression in patients with epilepsy
Stefanía Eyjolfsdóttir, Eugen Trinka, Yvonne Höller
Slow wave sleep duration and spectral abnormalities are related to both epilepsy and depression, but it is unclear how depressive symptoms in patients with epilepsy are affected by…
Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma
Tirtha Chanda, Katja Hauser, Sarah Hobelsberger +32
Although artificial intelligence (AI) systems have been shown to improve the accuracy of initial melanoma diagnosis, the lack of transparency in how these systems identify melanoma…
Vogtareuth Rehab Depth Datasets: Benchmark for Marker-less Posture Estimation in Rehabilitation
Soubarna Banik, Alejandro Mendoza Garcia, Lorenz Kiwull +2
Posture estimation using a single depth camera has become a useful tool for analyzing movements in rehabilitation. Recent advances in posture estimation in computer vision research…
Deep ROC Analysis and AUC as Balanced Average Accuracy to Improve Model Selection, Understanding and Interpretation
André M. Carrington, Douglas G. Manuel, Paul W. Fieguth +9
Optimal performance is critical for decision-making tasks from medicine to autonomous driving, however common performance measures may be too general or too specific. For binary cl…
Multivariate analysis of covariance when standard assumptions are violated
Georg Zimmermann, Markus Pauly, Arne C. Bathke
In applied research, it is often sensible to account for one or several covariates when testing for differences between multivariate means of several groups. However, the "classica…
Combining Heterogeneously Labeled Datasets For Training Segmentation Networks
Jana Kemnitz, Christian F. Baumgartner, Wolfgang Wirth +3
Accurate segmentation of medical images is an important step towards analyzing and tracking disease related morphological alterations in the anatomy. Convolutional neural networks…
Fully Convolutional Networks for Automated Segmentation of Abdominal Adipose Tissue Depots in Multicenter Water-Fat MRI
Taro Langner, Anders Hedström, Katharina Mörwald +5
Purpose: An approach for the automated segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in multicenter water-fat MRI scans of the abdomen was inv…
Sample size calculation and blinded recalculation for analysis of covariance models with multiple random covariates
Georg Zimmermann, Meinhard Kieser, Arne Bathke
When testing for superiority in a parallel-group setting with a continuous outcome, adjusting for covariates (e.g., baseline measurements) is usually recommended, in order to reduc…
Small-sample performance and underlying assumptions of a bootstrap-based inference method for a general analysis of covariance model with possibly heteroskedastic and nonnormal errors
Georg Zimmermann, Markus Pauly, Arne C. Bathke
It is well known that the standard F test is severely affected by heteroskedasticity in unbalanced analysis of covariance (ANCOVA) models. Currently available potential remedies fo…