Data Science and AI are key enablers for scientific discovery and revolutionize the way we do science and practice health and healthcare. However, an intrinsic challenge of working with AI methods is misuse, concerns with validity, accuracy, transportability and thus implementation, and other unwanted effects such as difficulties with explainability and transparency. The AI for Health working group encourages applications on fundamental or methodological research leading to improved trustworthiness, validation, transportability and transparency of AI innovations in the health and healthcare ecosystem.