Diagnostic Tool for Rare Diseases: Mathematics for Medicine How our researchers use mathematical models to detect rare diseases more quickly. © Patrick Pollmeier / Hochschule Bielefeld (HSBI) Diagnostic Tool for Rare Diseases: Mathematics for Medicine How Our Researchers Use Mathematical Models to Detect Rare Diseases More Quickly © Patrick Pollmeier / Hochschule Bielefeld (HSBI) Diagnostic Tool for Rare Diseases: Mathematics for Medicine How Our Researchers Use Mathematical Models to Detect Rare Diseases More Quickly Diagnostic Tool for Rare Diseases: Mathematics for Medicine How our researchers use mathematical models to detect rare diseases more quickly. © Patrick Pollmeier / Hochschule Bielefeld (HSBI) Diagnostic Tool for Rare Diseases: Mathematics for Medicine How Our Researchers Use Mathematical Models to Detect Rare Diseases More Quickly © Patrick Pollmeier / Hochschule Bielefeld (HSBI) Diagnostic Tool for Rare Diseases: Mathematics for Medicine How Our Researchers Use Mathematical Models to Detect Rare Diseases More Quickly Diagnostic Tool for Rare Diseases: Mathematics for Medicine How our researchers use mathematical models to detect rare diseases more quickly. © Patrick Pollmeier / Hochschule Bielefeld (HSBI)

Kaiserslautern. Detecting Rare Diseases Faster Thanks to Mathematical Models

Rare diseases affect more people than one might think, but they are often difficult to diagnose. On average, it takes years for patients to receive a diagnosis. In this project, our researchers are working with the pharmaceutical company Chiesi to develop a mathematical support tool that will help doctors identify rare diseases more quickly and test for them in a targeted manner.

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 AI in Decision Making at NTNU

Snow Ploughing and AI: A Case Study in Decision-Making   In late January, the AiD – Center for AI in Decision Making at Norwegian University of Science and Technology(NTNU)

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Darmstadt. Enhancing AMR Performance with Optimized PM Assembly

This post discusses recent advances in the collaborative project “OptiMag“, carried out between Magnotherm Solutions GmbH and TU Darmstadt.

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Linz. How layered media distort ultrasound images – and how to fix this using mathematics

by Simon Hackl I’m a PhD student at the Industrial Mathematics Institute at JKU Linz, working on improving ultrasound images. With my work, I contribute

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Gothenburg. Optimizing investments in and operation of Positive Energy Districts for emissions reductions

In recent years there has been an increased interest in finding cost efficient strategies to reduce the emissions of the building stock, in the effort

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Gothenburg. Making Sense of Lung Function Variability with Hidden Markov Models 

Respiratory diseases like asthma and chronic obstructive pulmonary disease (COPD) lowers quality of life and increases mortality. Much of this burden comes from exacerbations, acute

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Milano. Digital twins in orbit

In satellite space missions, the ability to extract information from sensor data is crucial to monitor the operational status of the satellite, to predict future

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Trondheim. Ethiopian Norwegian network in computational mathematics

Authors: Markus Grasmair (NTNU), Zerihun Kinfe Birhanu (Hawassa Univeristy) and Anne Kværnø (NTNU) The collaboration between Hawassa University in Ethiopia (HU) and NTNU goes back

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Trondheim. AID: AI for Decisions

AID is a recent NTNU initiative on Artificial Intelligence (AI) for Decision Making and a proposal for a National AI Center. It is a joint

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Darmstadt. Multiphysical simulation of a permanent magnet assembly for magnetocaloric refrigeration

Magnetocaloric cooling is an emerging technology for room temperature refrigeration. It has the potential to surpass the established gas-vapor compression refrigeration system in terms of

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