Future of explainable artificial intelligence research in healthcare
From September 2 to 6, 2024, the Faculty of Informatics and the Institute of Computer Science at Masaryk University in Brno hosted a successful summer school focused on Explainable Artificial Intelligence (XAI) in digital pathology. Organized by members of the BioMedAI project, the event attracted nearly 40 participants eager to explore the applications of AI in medicine.
The XAI Summer School has successfully started, with nearly 40 participants attending lectures by experts in the field. Renowned speakers are sharing valuable insights and inspiring the next generation to explore this high-potential area that promises significant advancements in medicine.
The EOSC Association Task Forces play a key role in the development of the European Open Science Cloud (EOSC). These teams, composed of experts and volunteers from across Europe, focus on specific areas essential for the implementation and advancement of EOSC.
From September 2 to 6, 2024, the Faculty of Informatics and the Institute of Computer Science at Masaryk University in Brno will host a summer school focused on Explainable Artificial Intelligence (XAI) in digital pathology. This educational program promises participants a comprehensive view of how artificial intelligence can be used in medical applications.
The non-profit organization Science Party hosted an event spotlighting the collaborative efforts of pathologists and IT specialists from the BioMedAI project as they presented the challenge of cancer using AI!
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.
“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