Session

Description Advances in Artificial Intelligence (AI) are reshaping life sciences and healthcare research. Our minisymposium explores AI's transformative role, delving into Computational Science, Computer Vision, and High-Performance Computing (HPC). Sessions span cancer research, personalized medicine, interactive machine learning, and privacy-preserving federated learning offering a panoramic view of AI's applications. In cancer research, Dr. Ellingson discusses the impact of developing models that integrate biological factors and social determinants of health using HPC. Precision imaging, spotlighted by Dr. Gichoya, leverages vast reservoirs of images to advance precision medicine while taking into account the serious ethical concerns. The minisymposium addresses the AI's black box challenge, crucial for trust and accountability. Dr. Jaeger shares human-centered approaches for recent developments in probabilistic modeling and explainable AI in cancer care. Challenges like data availability, scalability, and ethical AI practices are focal points. Dr. Madduri discusses federated learning's potential to build trustworthy AI in life sciences across institutions. The minisymposium aims to shape ethical standards, foster collaboration, and address the multifaceted challenges of guiding ethical AI integration in life sciences and healthcare. We aim to influence best practices and guidelines, propelling the synergy between AI and life sciences for the benefit of all of us.