Whether we are predisposed to particular diseases depends to a large extent on the countless variants in our genome. However in the case of genetic variants the influence on the presentation of certain pathological traits has been difficult to determine. Researchers have introduced an algorithm based on deep learning that can predict the effects of rare genetic variants.

Heidelberg Epignostix GmbH, a deeptech start-up committed to precision cancer diagnostics today announces €4.3M in seed funding. This investment will enable Heidelberg Epignostix to make a substantial leap forward in driving market development for its flagship indication for brain tumor classification.

Invasive infections such as sepsis require immediate and targeted treatment. Experts from the Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB and group partners have succeeded in establishing a reconceptualized detection principle that can make a crucial contribution to saving lives through fast, ultra-accurate pathogen identification. They have been chosen to receive the 2024 Stifterverband Science Prize for their efforts.

PhD student at Furtwangen University develops method for faster determination of antibiotic resistance. The increase in antibiotic-resistant pathogens and the associated treatment, which is a major problem in public healthcare facilities, is the subject of a research project at Furtwangen University.

Working with a new Emmy Noether Group, Dr. Pascal Schlosser is investigating how machine learning can aid in understanding the complex relationships between genes, proteins, and diseases.

How well do the algorithms used in the AI-supported analysis of medical images perform their tasks? This depends to a large extent on the metrics used to evaluate their performance. An international consortium led by scientists from the German Cancer Research Center and the National Center for Tumor Diseases has compiled the knowledge available worldwide on the specific strengths, weaknesses and limitations of the various validation metrics.

The German Research Foundation (DFG) has announced the first pivotal decisions for the "Clusters of Excellence" funding line as part of the Excellence Strategy of the German federal and state governments. The University of Stuttgart has been given the green light for two new cluster initiatives.

Artificial intelligence (AI) can help dermatologists to detect skin cancer. However, many dermatologists distrust the algorithms' decisions, which they cannot comprehend. Scientists at the German Cancer Research Center have now developed an AI-based support system for skin cancer diagnostics that explains its decisions.

The family-owned MedTech company KARL STORZ announces the acquisition of the innovative software manufacturer Innersight Labs Ltd. (ISL) headquartered in London. In addition to state-of-the-art endoscopes, high-end medical devices, and integrated solutions for the operating room, KARL STORZ is also continuing to expand in innovative software solutions.

University of Tübingen researchers reverse the evolution of a class of antibiotics to gain insights for the development of new drugs.

A research team of scientists from the Fraunhofer IPA, the Bosch Digital Innovation Hub at Bosch Health Campus and the Institute of Image-Guided Surgery (IHU) of Strasbourg has jointly launched the DAIOR project. Within the framework of the project, the project partners are working on realizing the operating room of the future with help of artificial intelligence and robot assisted telemedicine.

Current diagnostic methods do not always reliably distinguish between chronic inflammation of the pancreas and pancreatic cancer. About one third of all diagnoses are inconclusive. Scientists from the German Cancer Research (DKFZ) and from Heidelberg University Hospital (UKHD) therefore searched for molecular markers that could specify this diagnosis.

The computational design of new proteins for biomedical or other applications involves long computing times on powerful servers. A joint team of researchers from the Max Planck Institute for Biology Tübingen and the University Hospital Tübingen has now developed and tested a new computational method to greatly speed up the necessary energy calculations. Their framework allows for a precise and efficient design of functional proteins.

Scientists from the German Cancer Research Center (DKFZ) and the Cambridge Stem Cell Institute have developed an AI system that recognizes and characterizes white and red blood cells in microscopic images of blood samples. The algorithm can help physicians diagnose blood disorders and is available as an open source method for research purposes.

On Tuesday, July 18, 2023, the Tübingen AI Center held a symposium to celebrate its permanent establishment as a national AI center. Since July 1, 2022, it has received 20 million euros a year in funding from the federal government and the state.

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.