AI (Artificial Intelligence) + Healthcare refers to the application of artificial intelligence technology in healthcare-related fields. It involves building infrastructure and collecting data to apply AI technology and big data services to the healthcare industry, improving diagnostic efficiency and service quality, reducing the complexity and risks of various healthcare services, and addressing the growing demand for healthcare services. Simultaneously, as the healthcare field develops, more treatment options will emerge, further promoting the application of AI in various healthcare areas.
01
Development History and Current Status of AI in Healthcare
Artificial intelligence (AI) began to emerge as an independent research field in 1956, evolving through neural networks and fuzzy logic to deep learning, experiencing technological ups and downs. In China, the earliest application of AI in healthcare can be traced back to the "Guan Youbo Liver Disease Diagnosis and Treatment Procedure" in 1978. In 1996, companies focusing on AI research and development began to appear in my country. From 2000 to 2015, international research focused on AI applications outside of clinical knowledge bases, such as the implementation of surgical robots and the encouragement of electronic medical records. From 2015 to 2017, due to a significant improvement in the accuracy of AI in image recognition, AI+imaging experienced rapid development. After 2018, AI+healthcare in China entered a stable development stage, with new products such as smart medical records emerging. Currently, domestically produced surgical robots are still in the research stage. By 2018, over a thousand tertiary hospitals nationwide had introduced AI products.
AI in healthcare broadly refers to the application of artificial intelligence technologies, including but not limited to smart sensors, neural network chips, and open-source platforms, in the medical and health field. In the medical field, for example, hospital information systems lay the foundation for the intervention of medical AI. The working logic of artificial intelligence, from data acquisition to data processing and ultimately providing feedback, can be applied to various modules of the medical industry, including pre-diagnosis, diagnosis, and post-diagnosis.
02
Analysis of Investment and Financing in my country's AI + Healthcare Sector
With the continued rise in popularity of AI in healthcare both internationally and domestically, capital has focused more on it. While the number of healthcare financing events in my country decreased in 2020, the total amount raised surged, reaching a record high of nearly 4 billion yuan. AI-driven drug development was the most popular area for AI-driven healthcare financing. AI+imaging accounted for approximately 20% of the total financing amount for three consecutive years, becoming another popular area for financing. Comparing the financing rounds of 2019 and 2020, the proportion of angel, Series A, and Series B rounds decreased from 85.7% to 70.6%, indicating improved market maturity. The industry is currently in a period of rapid growth.
03
Latest policy direction for AI+healthcare in China
At the pharmaceutical industry level: Both supply-side reforms in pharmaceuticals and public hospital reforms have raised requirements for product innovation and information flow, driving technological innovation. At the technological innovation level: Emerging technologies are supporting healthcare reform and accelerating its upgrading. The development of emerging industries such as AI, big data, and cloud computing has provided new avenues for the healthcare industry, including smart hardware, AI-driven drug discovery, and 3D printing of human organs. Overall, healthcare policy reforms are in line with industry development trends, and policy-driven initiatives are further accelerating technological innovation and promoting the development and implementation of medical AI.
In 2017, my country's State Council issued the "New Generation Artificial Intelligence Development Plan," which proposed developing convenient and efficient intelligent services, promoting the application of new AI-based treatment models and methods, and establishing a rapid and accurate intelligent medical system. Since 2017, my country has promoted artificial intelligence as a national policy, repeatedly including it in government work reports. AI+healthcare, as a pioneer in AI, has received strong government support. In 2018, the government proposed extending AI to primary healthcare; in 2019, the scope of AI+healthcare was further expanded to include the health and wellness sector; and in 2020, future development guidelines were further proposed, with the aim of establishing a preliminary standard system and norms in the field of AI, particularly in healthcare, by 2023.
04
AI+Healthcare Industry Chain Analysis
The AI+core healthcare industry chain can be divided into three layers: the AI foundation layer, the AI medical technology layer, and the application layer.
1) At the foundational layer, apart from data services, strong technological barriers have been established in core areas such as chips and communications, resulting in an oligopolistic market.
2) At the technical level, algorithms, frameworks, and general technologies require long-term investment and R&D to overcome. Currently, major technology companies and internet giants have basically completed their layouts, leaving little room for small and medium-sized enterprises to survive.
3) Application layer: The application layer can reach all medical service scenarios, such as in-hospital clinical decision-making systems, surgical robots, smart medical record systems, medical imaging, new drug research and development and gene testing for pharmaceutical companies. A large number of Internet medical companies and traditional medical companies have entered this field, and a large number of startups relying on AI algorithms have emerged.
The development of AI-enabled healthcare involves providing intelligent services to multiple stakeholders. For healthcare institutions, the construction of smart hospitals encompasses the intelligent development of patients, medical care (including outpatient and inpatient services), nursing, medical technology (including pharmacy), management (including administration and operations), logistical support, teaching and research, and regional coordination—a systematic project. For regulatory agencies, the construction of intelligent supervision involves the oversight of medical data, medical practices, medical expenses, and medical personnel. AI needs to assist in achieving privacy protection and access control for medical data, ensuring the scientific and compliant nature of medical practices, the reasonableness and authenticity of medical expenses, and the flexibility of medical personnel organization.
Our intelligent services cater to the industry ecosystem, providing pharmaceutical companies with services in target discovery and exploration, compound screening and optimization, preclinical research, clinical research, registration and application, and real-world research. We also support medical device companies in developing AI-powered medical devices, offer intelligent consultation, intelligent prescription renewal, and intelligent patient management services to internet healthcare companies, intelligent distribution, intelligent pricing, and intelligent claims services to insurance companies, intelligent procurement, prescription processing, and patient management services to pharmacies, and imaging and pathology-assisted diagnostic services to third-party medical testing companies. Our patient-oriented intelligent management system includes services such as health management, online follow-up consultations, chronic disease management, rehabilitation nursing, and online medication purchase.
05
AI + Healthcare: Future Trends
1. AI is helping to continuously advance medical knowledge graphs, empowering multiple application scenarios such as clinical decision-making.
Medical knowledge graphs offer a more effective way to represent, organize, analyze, manage, and utilize massive, heterogeneous, and dynamic medical big data in healthcare information systems, thereby enhancing the system's intelligence and bringing it closer to human cognitive thinking. The construction process of a medical knowledge graph generally consists of four steps: medical knowledge representation, medical knowledge extraction, medical knowledge fusion, and medical knowledge reasoning. Thanks to the continuous advancements in artificial intelligence, significant progress has been made in all four steps.
2. Overcome AI technology barriers and achieve deeper integration with the medical field.
The deep integration of healthcare and artificial intelligence is an inevitable trend. Future technological breakthroughs in AI+healthcare will include further optimization of algorithm fit, enhanced algorithm versatility, protection of privacy information, improved interpretability of AI+healthcare results, and continuous reduction of the risk of adverse medical events through increased reliable verification. Looking at the development trend of the AI+healthcare industry, with the advancement of technologies such as artificial intelligence, mobile internet, the Internet of Things, big data, and big data security, all aspects of the health management process will become increasingly intelligent, and precision medicine will become increasingly personalized and individualized.
In the future, with the outstanding algorithms and big data analysis of AI+healthcare, data barriers between various service ports of related service platforms will be gradually broken down, achieving perfect implementation in various core application scenarios and ultimately improving the overall level of healthcare in China.
