 AI is not individual work, but teamwork. My name is Kuan Yeoh-Shi and I focus on deep learning for computer-aided diagnosis and for radionuclide therapy optimization. As a computer scientist doing research at the Department of Nuclear Medicine in the Spital, I have the opportunity to work very closely with the clinical management and Professor Axl Rominger. This allows me and my lab for AI and translational serenostics to profit directly from the clinical expertise of the healthcare professionals. Nuclear medicine is a continuously growing interdisciplinary field with lots of potentials but also challenges. I am excited to develop artificial intelligence methods to tackle these challenges and explore the potentials of nuclear medicine. Here at the Department of Nuclear Medicine, we are operating a cutting-edge total-body PET-30 scanner. However, the potential of the big data of the ultra-high sensitivity acquisition is not fully explored. This is why we are developing AI methods to enhance the detector efficiency, signal utilization, imaging reconstruction, and biomarker extraction. This will consequently improve the diagnostic accuracy while reducing radiation exposure for patients. Our clinic uses advanced imaging to personalize patient treatment, in particular for molecular radiotherapy. Based on pre-therapeutic imaging, AI is developed to predict the radiation dose and radiobiological effects for each patient. AI-based treatment planning will support the adjustment of injection dose or treatment cycles to improve the treatment outcome while minimizing the side effects. The fascinating thing about artificial intelligence in my field is that it can integrate informatics with physics, chemistry, biology, and medicine. KNIME offers me a whole new opportunity to improve the receptability to new technologies. This will enable both clinicians and engineers to develop a shared broad vision of the possibilities of AI in health care for the benefit of patients.