Preparing for the Ai Era Under the Digital Health Framework Information and communication technology (ICT) for health has shown great potential to improve healthcare efficiency, especially artificial intelligence (AI). To better understand the influence of ICT technology on health, a framework of the digital health industry has been proposed in this paper. Factors from the health industry and the ICT part are extracted to study the interaction between two groups of component factors. Health factors include service and management; and ICT factors include sensors, networks, data resources, platforms, applications and solutions. The interaction between ICT and health can be traced through the development history, from the stage of institutional informationization to regional informationization, and finally to service intelligentization. Following such a developmental roadmap, AI was chosen as one of the most powerful technologies to study the penetration effect and key development trends from the perspectives of data, computing power and algorithms. The health industry will be much improved or redefined in the coming AI era. To better understand the strengths, weaknesses and limitations of AI for health, exogenous factors are discussed at the end of the paper; preparations on collaboration mechanism; standardization and regulation have been proposed for the sustainable development of digital health in the AI era.

Towards International Standards for the Evaluation of Artificial Intelligence for Health Healthcare can benefit considerably from advanced information processing technologies, in particular from machine learning (ML) and artificial intelligence (AI). However, the health domain only hesitantly adopts these powerful but complex innovations so far, because any technical fault can affect peopleu0027s health, privacy, and consequently their entire lives. In this paper, we substantiate that international standards are required for thoroughly validating AI solutions for health, by benchmarking their performance. These standards might ultimately create wellfounded trust in those AI solutions that have provided conclusive evidence to be accurate, effective and reliable. We give reasons that standardized benchmarking of AI solutions for health is a necessary complement of established assessment procedures. In particular, we demonstrate that it is beneficial to tackle this topic on a global scale and summarize the achievements of the first year of the ITUWHO focus group on xe2x80x9cAI for Healthxe2x80x9d that has tasked itself to work towards creating these evaluation standards.