Algorithms from artificial intelligence (AI) are being used more and more frequently, also for medical diagnosis. However, their potential is barely being tapped in a number of areas. A collaborative project from Universitätsklinikum Erlangen (UKER) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Gravina Hospital in Caltagirone (Italy) is showing that it does not need to be that way. The researchers are demonstrating how AI can be seamlessly integrated into clinical practice in a fully digitized department of pathology.

Their findings have now been published in the journal Genome Medicine. AI algorithms can help pathologists find the answers to these and other questions, for example by highlighting malignant transformation in digitalized tissue samples. However, their full potential often still remains untapped today. This is due in part to examination methods: while an MRI or ultrasound scan can produce digital images that can be assessed directly using AI, that is not the case with a tissue sample.

Until now, samples have mainly been examined using microscopes, explains PD Dr. Fulvia Ferrazzi who leads the working group for bioinformatics and computer-assisted pathology at the Department of Nephropathology (head: Prof.Dr. Kerstin Amann) and at the Institute of Pathology (director: Prof. Dr. Arndt Hartmann) at UKER. Digitalizing histopathological samples to obtain high-resolution images remains an exception.

The Department of Pathology (director: Dr. Filippo Fraggetta) at Gravina Hospital in Caltagirone in Italy is already a step ahead they routinely digitalize all tissue samples. The problem here is not the availability of digital data, comments Miriam Angeloni, who is pursuing a doctoral degree in Ferrazzi’s working group. Rather, there has been no way of analyzing these data automatically using deep learning models until now. This is the reason why AI tools are not yet routinely integrated into clinical diagnosis. We investigated how we could integrate the use of these tools more smoothly.

Source: https://www.fau.eu/2025/06/news/how-ai-can-be-integrated-seamlessly-into-pathological-diagnosis/#:~:text=During%20their%20collaborative%20project%2C%20the,server%20with%20various%20AI%20models