Healthcare industry

Proteins have characteristic amino acid sequences, the analysis of which is fundamental for research and medicine. These can be decoded; however, so-called protein sequencing is expensive and time-consuming. A large-scale research project led by Prof. Dr. Jan Behrends from the Institute of Physiology at the University of Freiburg now aims to establish a new technology for protein sequencing using nanopores, which will be rapid and cost-effective.

How can camera images be used during minimally invasive surgeries to assess whether the operated organ is sufficiently perfused with blood? Scientists from the German Cancer Research Center (DKFZ) and the Städtisches Klinikum Karlsruhe have now succeeded in automatic monitoring of ischemia during a kidney surgery using only the optical properties of the tissue and not relying on injection of contrast agent.

Automated pain recognition - 25/01/2023

Using artificial intelligence to improve pain management

Psychologists from Ulm and their cooperation partners have developed algorithms for automated pain recognition in order to be able to dose painkillers more precisely. The researchers are now looking for industrial partners to take their project to application.

Using new microscopic methods in combination with machine learning-based image analysis, researchers from Freiburg have discovered new structures on the surface of living B cells that affect the distribution and possibly the function of their antigen receptors. The researchers' study has been published in The EMBO Journal.

The newborn's immune system is suddenly confronted with microorganisms, food and numerous environmental influences at birth. How do the baby's immune cells prepare for this moment during pregnancy and birth? How do external influences shape the immune system immediately after birth? And what influence does an event like a premature birth have?

The nuclease Cas13b associated with the CRISPR gene scissors, which is an enzyme that degrades nucleic acids, has the potential to be used in the future in hereditary diseases to switch off unwanted genes. In the fight against infections, this nuclease is also being researched as an antiviral agent, as Cas13b can specifically intervene in the genetic material of viruses and render them harmless.

Company profile: medicalvalues GmbH - 05/05/2022

medicalvalues – best possible diagnostics thanks to AI

The Karlsruhe-based start-up medicalvalues GmbH wants to use its platform to bring together different clinical data sets and thus enable comprehensive medical diagnostics. Artificial intelligence featuring innovative diagnostic algorithms is used to evaluate the data and generate new insights for laboratories and hospitals.

In the field of optogenetics, scientists investigate the activity of neurons in the brain using light. A team led by Prof. Dr. Ilka Diester and Dr. David Eriksson from the Optophysiology Laboratory at the University of Freiburg has developed a new method to simultaneously conduct laminar recordings, multifiber stimulations, 3D optogenetic stimulation, connectivity inference, and behavioral quantification on brains.

Genetic alterations that promote the development and spread of tumors are difficult to identify. This is especially true for mutations in the non-protein-coding regions of the genome, which include all important regulatory sequences. Scientists at the German Cancer Research Center have now published an algorithm that detects cancer drivers in both the protein-coding and non-coding regions of the genome.

An international study with about 3000 patients confirms the validity of a new classification system for meningiomas. It combines tissue characteristics (histology) with molecular analyses and thus improves therapy planning.

Cyber Valley researchers have created medical educational tools that could potentially train the surgeons of the future, much like flight simulators train pilots. The team developed a range of artificial organ phantoms to serve as training platforms for surgeons. Thanks to the structured data of experienced medical professionals, a quantitative and objective assessment of a trainee’s skills can be assessed in real time.

Scientists use super-resolution microscopy to study previously undiscovered cellular worlds, revealing nanometer-scale details inside cells. This method revolutionized light microscopy and earned its inventors the 2014 Nobel Prize in Chemistry. In an international collaboration, AI researchers from Tübingen have now developed an algorithm that significantly accelerates this technology.

Scientists from the German Cancer Research Center and Heidelberg University Hospital have for the first time been able to delay the development of hereditary colorectal cancer with a protective vaccination. Mice with a hereditary predisposition to colorectal cancer survived significantly longer after vaccination than unvaccinated animals. Combining the vaccination with an anti-inflammatory drug increased the protective effect.

Article - 08/07/2021

Individual operation risk assessment by the Cognitive Medical Assistant

Despite modern surgical techniques and anaesthetic procedures, serious complications can occur during surgical interventions. An interdisciplinary team at Heidelberg University Hospital has launched a project called the Cognitive Medical Assistant (German: Der Kognitive Medizinische Assistant, KoMed for short), designed to better assess the individual risk of these interventions. The project’s goal is to systematically and comprehensively analyse…

Scientists from the EMBL and the German Cancer Research Center have presented a new method for generating metabolic profiles of individual cells. The method, which combines fluorescence microscopy and a specific form of mass spectroscopy, can analyze over a hundred metabolites and lipids from more than a thousand individual cells per hour. Researchers expect the method to better answer a variety of biomedical questions in the future.

AI-based evaluation of medical imaging data usually requires a specially developed algorithm for each task. Scientists from the German Cancer Research Center (DKFZ) have now presented a new method for configuring self-learning algorithms for a large number of different imaging datasets – without the need for specialist knowledge or very significant computing power.

The great potential of artificial intelligence (AI) and machine learning for the life sciences – from basic research in biology to medical applications – has largely been neglected to date. A new research unit aims to support AI research in the life sciences and to forge international links with the activities in Heidelberg.

Article - 09/10/2019

Epigenomics from the Cyber Valley

Cyber Valley Stuttgart-Tübingen is a European hotspot for artificial intelligence and home to many renowned experts and scientists. They are now joined by Gabriele Schweikert, who heads up the Computational Epigenomics research group in the Cyber Valley’s Division of Computational Biology. Schweikert is interested in exploring epigenetic mechanisms using machine learning methods.

Article - 21/02/2019

Using neuromedical artificial intelligence responsibly

Brain-computer interfaces are the latest developments in the neurotechnology field. They are used to record brain activity, which is then decoded with artificial intelligence techniques and converted into control signals for robots or computers. While this brings hope to severely paralysed people, it also implies risks due to the interest of companies like Google and Facebook in this type of data.

Article - 07/02/2019

Artificial intelligence in ophthalmology

Retinal diseases such as age-related macular degeneration (AMD) are now treatable. However, it is hard to predict individual disease progression. A group of researchers at the University Eye Centre in Freiburg are currently developing a new system which is hoped will allay fears and improve therapy planning. The system uses artificial intelligence to predict therapeutic outcome from image and patient data. Initial results are already available.

Article - 30/01/2019

candidum – computer-assisted enzyme design

Industry has been using enzymes for over a hundred years. While it initially had to content itself with natural enzymes, it is now increasingly possible to design tailor-made biocatalysts with specific properties. The start-up company candidum GmbH from Stuttgart promises to achieve this faster than ever before - mostly thanks to accelerated virtual screening.

Article - 02/10/2018

Artificial intelligence in the life sciences: machines as assistants

Artificial intelligence is currently one of the most innovative issues, but also one of the most controversial research areas. It already has a firm footing in many areas of our everyday life and often we are not even aware of it. Artificial intelligence has long been an integral part of many processes in research and diagnostics in medicine and the life sciences – and it will be even more widely used in the future.

University takes next hurdle in the German government’s Excellence Strategy funding program. The University of Tübingen is to have three new Clusters of Excellence.As part of the German government’s Excellence Strategy funding forhigher education research, Tübingen will host new outstanding research networks starting in January 2019. Representatives of Germany’s higher education policymakers announced the decision in Bonn on Thursday.

Article - 14/08/2018

Simple and fast: new optical method for analysing living cells

The junior researchers Dr. Daniel Geiger, Tobias Neckernuß and Jonas Pfeil from Ulm have developed an innovative method for non-contact real-time analysis of cells and other particles. The analysis involves low data rates and correspondingly little effort. This is what makes the method so attractive for medical applications.

Big Data - 26/03/2018

Eliciting reliable information from big data with classifiers and multimodal data fusion

Prof. Hans A. Kestler knows a great deal about large amounts of data. He heads up the Institute of Medical Systems Biology at the University of Ulm and is constantly inundated with cooperation enquiries from clinicians. On behalf of BIOPRO, Walter Pytlik asked him whether the conditions for using big data more in biomedical research are already largely present.