Jun Yan, the firm's chief technician, has been invited to share insights on addressing the challenges of AI applications in the healthcare industry.
[Hong Kong - September 8, 2021 - Yidu Tech Inc.] – The Publisher of the New England Journal of Medicine (NEJM) and Jiahui Medical Research and Education Group (J-Med) have recently co-hosted the 'AI in Medicine Symposium' (AIMS) in Shanghai. Dr. Jun Yan, CTO and Chief AI Scientist of Yidu Tech (2158:HK), was invited to share the company's experience in applying AI and big data to empower the healthcare industry, joining the discussion on the technology roadmap and prospects of 'Healthcare + AI.'
It was the first event on medical AI that the organizers have held in China. Twenty-five leading experts in medical, research and business communities gathered to discuss some of the hottest topics relating to medical AI, such as research guidelines, AI ethics, data governance and the latest advancements in this field.
Dr. Jun Yan pointed out that data governance is the primary challenge to achieving breakthroughs in medical AI innovation. Such data governance includes standardized management of data quality, computability, traceability and data security and compliance requirements. Amid the positive market prospects of AI applications for the healthcare industry, standardized data governance is critically essential for the whole sector to utilize heterogeneous medical data. This is required for industry players to apply complex medical data in a compliant and effective manner, leading them to build unbiased, high-quality AI models and yield professional insights, thereby supporting clinical decisions and medical research.
According to Dr. Yan, it is imperative to overcome three significant challenges – two on 'translation' and one on 'computation' – to achieve breakthroughs in AI application in healthcare. The first challenge on translation is to make raw data accumulated through human knowledge and behavior become computable data, supporting medical institutions to generate insights from datasets that can be understood and analyzed. The second challenge on translation is making the inference process and conclusion of the AI model understandable to humans. This will enable efficient human-machine collaboration, which will help hospitals to provide better medical services to patients and accelerate medical research. The challenge with computation is to make decentralized data accessible but invisible to data processors as supported by algorithms and computing capabilities, thus ensuring data security and privacy. Putting it into practice will require joint effort across the industry, both technology development, and mechanism build-out. Yidu Tech has been focusing its R&D and innovation on addressing these three challenges.
Upholding the vision of "green healthcare empowered by data intelligence," Yidu Tech has been extensively investing in R&D since its establishment in 2014. Its proprietary data intelligence infrastructure, YiduCore, which integrates medical insights and AI technologies, provides a range of services in clinical diagnosis, medical research, public health, new drug development and health management to various stakeholders in the healthcare sector, driving the transformation of healthcare services from information-based solutions to data-intelligence-based solutions.
Founded in 2014 with a mission "to make value-based precision healthcare accessible to everyone" and a vision of "green healthcare empowered by data intelligence," Yidu Tech Inc. focuses on addressing pain points in the digital transformation of the healthcare industry through its technological advantages in artificial intelligence. Leveraging YiduCore, a proprietary data intelligence infrastructure, Yidu Tech aims to provide the healthcare industry with innovative solutions driven by data intelligence, build a healthcare big data infrastructure, and promote the country's 'Healthy China 2030' initiative.