Healthcare is expected to benefit substantially from the recent revolutionary progress in artificial intelligence (AI), because it deals with huge amounts of data on a daily basis, such as patient information, medical histories, diagnostic results, genetic data, hospital billing, and clinical studies. This huge pool of data can train AI to detect patterns and make predictions and recommendations, substantially reducing the uncertainties that professionals face. The AXA chair will focus on the development of novel AI technologies, called neuro-symbolic cognitive systems, (1) to make better and less expensive diagnoses, (2) to optimize and personalize the treatment of patients, and (3) to prevent diseases, by collecting and using readily available life data from human beings (e.g., via fitness trackers and wearables). This will substantially reduce the costs of healthcare, improve its availability, and increase the life span and well-being of human beings. A crucial aspect of the technologies to be developed will be the ability (4) to explain the generated outputs: stakeholders in healthcare need to know how a system produces a diagnosis or recommendation. Furthermore, this explainability will also improve the medical understanding of diseases and their treatments. Besides also contributing to the AI community with novel explainable AI systems, the expected results of this research will thus also contribute to producing new medical insights and progress. The above goals (2) and (3) will also allow for a more accurate risk prediction and the possibility for risk reduction, by choosing a risk-minimizing treatment and lifestyle, respectively, within means/resources available.