A recent study, currently available as a preprint, was conducted by an international team of researchers led by Olivia I. Coleman and Adam Sorbie, with contributions from numerous others, including Tim Kacprowski (see complete author list below). It highlights how cellular stress responses in intestinal cells can contribute to the development of colorectal cancer by […]
We are pleased to announce the online publication of the book, “Zusammenwirken von natürlicher und künstlicher Intelligenz: Beurteilen – Messen – Bewerten” (Interaction of Natural and Artificial Intelligence: Assessing – Measuring – Evaluating)! The book addresses interdisciplinary perspectives on how humans and machines can coexist and collaborate in the future. Key topics include medicine and
The Peter L. Reichertz Institute for Medical Informatics has developed MeTEor (MEtabolite Trajectory ExplORer), an R Shiny app designed to simplify the analysis of longitudinal metabolomics data. MeTEor addresses challenges such as data complexity and temporal variability, providing researchers with accessible tools for exploring time-series omics datasets without requiring advanced programming expertise. To demonstrate its
MeTEor: A New R Shiny App for Longitudinal Metabolomics Analysis Read Post »
Large Language Models” (LLMs), such as ChatGPT, could potentially support the informed consent process for surgical interventions, although the full extent of their capabilities remains unclear. A recent study by TU Braunschweig and Medizinische Hochschule Hannover investigates whether advanced AI systems can make medical information more understandable while easing the workload on medical personnel. However,
Opportunities and Limits of “Simulated Empathy”: LLMs in Surgical Informed Consent Read Post »
As part of an international research team led by Olga Tsoy from the University of Hamburg, the Division of Data Science in Biomedicine contributed to the development of new guidelines for determining the optimal sequencing depth in RNA sequencing (RNA-Seq) studies focusing on alternative splicing (AS). By analyzing extensive RNA-Seq datasets from human tissues such
New Recommendations for Optimal Sequencing Depth in Alternative Splicing Studies Read Post »
As part of an international research team led by Olga Tsoy from the University of Hamburg, the Division of Data Science in Biomedicine contributed to the development of new guidelines for determining the optimal sequencing depth in RNA sequencing (RNA-Seq) studies focusing on alternative splicing (AS). By analyzing extensive RNA-Seq datasets from human tissues such
New Recommendations for Optimal Sequencing Depth in Alternative Splicing Studies Read Post »
