AI Agents Transforming Oncology Research and Clinical Decision-Making
This Collection delves into AI agents in oncology, covering autonomous and multimodal systems for clinical decision-making, workflow automation, reasoning, and trustworthiness.
Dr. Vanja Mišković, a Postdoctoral Researcher at Politecnico di Milano and a professional collaborator at Fondazione IRCCS Istituto Nazionale dei Tumori in Milan, is at the forefront of integrating artificial intelligence (AI) into oncology. Her work focuses on developing explainable machine learning and deep learning models to enhance clinical decision-making, particularly in immunotherapy treatment response prediction and patient stratification.
Key Research Areas
- Explainable AI for Oncology: Dr. Mišković specializes in creating transparent AI models that clinicians can trust. Her research leverages real-world clinical data, radiomics, and multimodal approaches to build decision-support tools.
- Foundation Models: She is exploring the potential of foundation models for medical imaging and tabular clinical data to improve predictive performance and generalizability.
- AI-ON-Lab: As a co-leader of the AI-ON-Lab (Artificial Intelligence in Oncology Lab), she fosters interdisciplinary collaboration among engineers, data scientists, and clinicians to tackle challenges in precision oncology.
Impact on Clinical Workflows
Dr. Mišković's research extends to how AI agents—both predictive and generative—can augment oncology workflows. Her projects involve multi-modal data integration and clinical evaluation of AI models, with a strong emphasis on transparency, usability, and fairness.
Career and Collaborations
Dr. Mišković earned her PhD in Engineering and Technology from Université libre de Bruxelles in 2021. Her current role at Politecnico di Milano and Fondazione IRCCS Istituto Nazionale dei Tumori underscores her commitment to translating AI methodologies into practical, clinically useful tools.
Future Directions
Her ongoing work aims to personalize treatment strategies and improve the trustworthiness of AI systems in oncology, ensuring they meet the highest standards of clinical utility and ethical consideration.
For more information, visit Politecnico di Milano and Fondazione IRCCS Istituto Nazionale dei Tumori.
Related News
Lenovo Wins Frost Sullivan 2025 Asia-Pacific AI Services Leadership Award
Lenovo earns Frost Sullivan's 2025 Asia-Pacific AI Services Customer Value Leadership Recognition for its value-driven innovation and real-world AI impact.
Baidu Wenku GenFlow 2.0 Revolutionizes AI Agents with Multi-Agent Architecture
Baidu Wenku's GenFlow 2.0 introduces a multi-agent system for parallel task processing, integrating with Cangzhou OS to enhance efficiency and redefine AI workflows.
About the Author
Dr. Lisa Kim
AI Ethics Researcher
Leading expert in AI ethics and responsible AI development with 13 years of research experience. Former member of Microsoft AI Ethics Committee, now provides consulting for multiple international AI governance organizations. Regularly contributes AI ethics articles to top-tier journals like Nature and Science.