Making AI-supported radiology more transparent and reliable The TRUST-RAD project developed AI tools for radiology that are not only powerful but, above all, reliable and transparent. The focus was on the development of RadVLM, an innovative AI model for analysing chest X-rays. The model can explain findings, draft reports, answer… Read More »Project closure: TRUST-RAD
The TRUST-RAD project team has published a comprehensive dataset for the development of AI assistance systems for X-ray image interpretation. RadVLM Instruction Dataset is now available to the scientific community on the PhysioNet platform. The dataset comprises over 1.1 million image-instruction pairs from chest X-rays and covers various radiological tasks:… Read More »TRUST-RAD: New dataset for reliable AI assistance tools in radiology published
A paper by the TRUST-RAD research team, in collaboration with the Medical Data Science group at ETH Zurich, and the computational infrastructure supported by the Swiss AI Initiative and the Swiss National Supercomputing Centre (CSCS) under project ID a02 on Alps, has been accepted for the ICML 2025 Workshop on… Read More »Reliable AI assistance tools for radiology: TRUST-RAD represented at ICML 2025 workshop
A radiologist in a large hospital sees hundreds of chest X-rays (CXRs) daily and must make quick and accurate diagnoses. The sheer volume of images is overwhelming, and there are not enough radiologists to analyze all the images promptly. This is where RadVLM comes into play. RadVLM is an innovative… Read More »AI Supports Chest X-Ray Analysis: RadVLM
The funded projects deal with data protection and digital self-protection, media literacy and digital resilience as well as AI assistance and trust in new technology. Current developments such as artificial intelligence (AI) and increasingly easy access to digital tools are accelerating and expanding the range of possibilities in the creative… Read More »DIZH promotes digital resilience and media literacy with innovative projects