BioMedAI TWINNING
Future of explainable artificial intelligence research in healthcare
News
Provenance of specimen and data – A prerequisite for AI development in computational pathology
December 2023
Shedding light on the black box of a neural network used to detect prostate cancer in whole slide images by occlusion-based explainability
December 2023
Privacy Risks of Whole-Slide Image Sharing in Digital Pathology
May 2023
AI for life: Trends in artificial intelligence for biotechnology
May 2023
Pathologist Rudolf Nenutil featured on Czech Radio podcast: Discussion on Software Development utilizing artificial intelligence for cancer detection
Pathologist Rudolf Nenutil recently appeared as a guest on a popular Czech Radio podcast, where he shared insights into the development of software utilizing artificial intelligence for the detection of cancerous findings.
Petr Holub, BioMedAI representative, contributes to discussion on FAIR data and the impact of AI on research
In late January, a discussion regarding the significance of integrating FAIR data into scientific research occurred in Milan. The event ESFRI-EOSC Policy Workshop on "FAIR Data Productivity and Advanced Digitalization" brought together representatives from European research infrastructures to delve into the future of research.
“The increasing demand for sophisticated clinical diagnostics leads to the need for semi-automatic systems using AI and machine learning to speed up the diagnosis process, and the BioMedAI project aims to establish close cooperation between computer science and clinical experts to develop explainable and trustworthy AI solutions through virtual training, workshops, and summer schools, while also increasing the visibility and presence of explainable AI research in healthcare.”
Petr Holub, Project Lead