Artificial intelligence (AI) has been widely applied in healthcare, such as in medical literature mining, medical image interpretation, and medical records analysis. By offering decision supports in diagnosis and treatment, it allows healthcare providers to focus more on professional tasks, thus delivering more valuable services. Medical centers in Taiwan have been accumulating a significant amount of clinical data, which would be the solid foundation for fostering the smart healthcare industry.
According to the conclusions of the BioTaiwan Committee (BTC) meeting, the goals for the year 2020 were: (1) to promote the pilot program of precision medicine; (2) to build a precision healthcare system through Real-world evidence (RWE)/Real-world data (RWD) with the association with genetic information and clinical data. And the goal for the year 2021 was “continuously investing in AI and/or machine learning (ML) for the applications in disease detection and diagnosis, healthcare management, and in quality controls for pharmaceutical products and medical devices manufacturing”. In response to the policy and vision of biotechnology development, the project, “The interdisciplinary development and technology project using AI and clinical database”, was launched by government to accelerate the development of medical AI in Taiwan.
Clinical data includes patient’s personal information and a variety of medical records such as pathology, radiological images, laboratory tests, and so on. The establishment of a medical AI system and following applications rely on not only the tremendous quantity but also the integrity and comprehensiveness of datasets. In light of this, the project aims to leverage the power of AI industry and medical centers’ valuable datasets (including radiomics, genomics and clinical Informatics), promoting a cross-industrial and value-added collaboration for the development of smart healthcare industry.
To take the clinical unmet needs as the start point, the government launched the project to bring medical centers and ICT manufacturers together. We set the milestones of the project as topic targeting, technology development, patent preparation, clinical validation, and practical implement. The end-points would be to incorporate AI healthcare startups, thus establishing a successful model for AI application in healthcare. The key points of the project are listed below:
1. To accelerate the cross-disciplinary, cross-regional, and cross-border hospital cooperation in research and development of medical AI.
2. To cultivate talents in cross-disciplinary technologies, such as medical informatics, ICT, and big data analysis.
3. To optimize medical interpretation systems/platforms and to improve clinical diagnosis and treatment through AI algorithms.
4. To promote health and well-being and to prevent diseases by applying AI technology and clinical information
5. To establish and promote the successful models of research and development in artificial intelligence for healthcare.