China's Health System and the Role of AI
China’s hospitals are in the midst of one of the most ambitious digital shifts in global healthcare. Walk into major healthcare centres in Beijing, Shanghai, or Shenzhen and you’ll see glimpses of what the future might look like: radiologists reviewing AI-annotated scans, oncologists working with machine-structured real-world data, and nurses guided by clinical copilots trained on vast national datasets. Together, these efforts form the early architecture of an AI-enabled healthcare system taking shape in real time.
It's important to acknowledge that this transformation isn’t smooth or uniform. Just like many countries across the world, China’s health system still wrestles with inconsistent data quality, uneven digital infrastructure, regional capability gaps, and clinician scepticism - especially outside top-tier hospitals. Policy ambition often moves faster than the realities on the ground. But even with these headwinds, a handful of companies are breaking through: securing approvals, deploying at scale, and solving immediate workflow challenges rather than simply riding the AI hype cycle.
For Western readers, this moment is worth watching. Not because China is racing ahead unchecked, but because it shows how AI in healthcare evolves when a system pushes aggressively toward digitisation, even amid structural friction. The progress - and the limitations - offer lessons for anyone thinking about where clinical AI may realistically deliver impact next.
The Chinese AI Healthcare Companies to Watch
Below, we highlight eight Chinese AI-healthcare companies with verifiable traction across imaging, data infrastructure, and clinical workflow support. AI-drug-discovery firms will be covered separately in a future article.
Infervision
Founded: 2016
Headquarters: Beijing
Core focus: Radiomics and AI-powered medical imaging for lung, chest, and cardiovascular disease.
Flagship platforms:
- InferRead series of image analysis solutions primarily focussed on lung morbidities
- InferOperate series of 3D reconstruction solutions focussed on thoracic, liver and urology surgeries
Why it matters:
Infervision has translated AI-imaging into routine hospital workflows at meaningful scale. With integrations across major PACS systems, multi-modality support (CT, DR, MRI), and regulatory clearances spanning NMPA, CE, FDA, PMDA, and UKCA, the company demonstrates strong commercial maturity. It reports operations in 30 countries with five global offices, positioning it as one of the most internationally visible players in China’s medical-AI landscape.
Shukun Technology (CareVerse in Global markets)
Founded: 2017
Headquarters: Beijing
Core focus: AI-powered “Digital Body” imaging platform, with a particular strength in cardiovascular and cerebrovascular disease.
Flagship platforms:
- The DigitalDoc and Digital Doctor platforms, covering heart, brain, chest, abdomen and musculoskeletal imaging across CT, MRI, DR, ultrasound and more.
Why it matters:
Shukun has gained wide deployment across China, claiming adoption in 4,000 public hospitals and 1,000 medical-examination institutions. Its positioning as a workflow-focused platform, supporting quality control, structure recognition, and standardised diagnosis across sites, gives it relevance in large care systems where demand for cardiovascular imaging expertise outpaces supply.
Yidu Tech
Founded: 2014
Headquarters: Beijing
Core focus: Healthcare data infrastructure and AI platforms for hospitals, public health systems, and biopharma.
Flagship platform:
- YiduCore, a platform that powers a suite of applications across clinical care, staff education, hospital management and research.
Why it matters:
Where Infervision and Shukun work on pixels, Yidu Tech works on data exhaust. Yidu Tech claims coverage of over one billion patient records across thousands of institutions, giving it a rare footprint in healthcare data infrastructure. By supporting operational tasks such as triage, scheduling, documentation and clinical interpretation, it plays an important role in digitisation efforts within large public-hospital networks. Its platforms were reported to have helped cities manage pandemic tracing and treatment logistics, documented in a sponsored Nature article as emblematic of China’s data-driven Covid response.
Deepwise
Founded: 2017
Headquarters: Beijing
Core focus: Radiomics and AI imaging solutions across multiple organs, with particular focus on breast cancer screening.
Flagship platform:
- Dr. Wise platform for assisted clinical diagnosis and research
Why it matters:
Deepwise has achieved regulatory traction in important disease areas, including what it claims were China’s first NMPA Class III AI certificates for pneumonia (2021) and breast-cancer mammography screening (2023). That regulatory progress, paired with focus on a clearly defined set of clinical use cases, suggests a pragmatic commercial strategy with measurable clinical impact.
LinkingMed
Founded: 2014
Headquarters: Beijing
Core focus: AI-powered auto-contouring, treatment-planning, and cloud-based collaboration tools to streamline and scale radiotherapy workflows in hospitals and imaging centers.
Flagship platform:
- RT-Viewer-contour, an AI software tool that helps clinicians identify, outline, and label tumors and critical organs on medical scans so radiation can be precisely targeted to cancer while avoiding healthy tissue.
Why it matters:
As demand for radiotherapy grows faster than specialist capacity, LinkingMed’s automation of contouring, planning, and QA supports hospitals under operational strain. By embedding into radiotherapy workflows, the company occupies a strategic position in one of the fastest-expanding areas of oncology care.
Airdoc
Founded: 2015
Headquarters: Beijing
Core focus: AI-powered retinal imaging to assess eye disease and systemic risk via a single fundus photograph.
Flagship platform:
- Airdoc-AIFUNDUS, a platform for the rapid diagnosis and assessment for diabetic retinopathy.
Why it matters:
Airdoc claims to have screened more than 30 million patients and to have been the first medical-AI company listed on the Hong Kong Stock Exchange (2021). With Class III NMPA approval for diabetic-retinopathy screening, it addresses a major national health priority: early management of rising diabetes and cardiovascular-risk burden through scalable, non-invasive screening.
SenseTime
Founded: 2014
Headquarters: Hong Kong
Core focus: Multi-modality imaging platform, smart-hospital solutions, and AI-assisted clinical workflows.
Flagship platforms:
- SenseCare, a suite of AI toolkits covering segmentation, registration, lesion detection and 3D visualisation across multiple imaging modalities and body regions.
Why it matters:
SenseTime is one of the most established companies in China’s AI sector, listed on the Hong Kong Stock Exchange and operating across multiple technology verticals. Its SenseCare medical platform positions the company as a general-purpose layer for AI-assisted hospitals. Clinical reports and media coverage suggest it can significantly enhance imaging-department efficiency, strengthening its role in large hospital networks.
Xunfei Healthcare
Founded: 2016
Headquarters: Beijing
Core focus: Comprehensive AI healthcare stack across clinical decision support, disease and patient management, imaging and even insurance.
Flagship products:
- AI-assisted history taking, triage and diagnosis support
- Voice-driven EMR and clinical documentation tools
- Remote imaging cloud & telemedicine service platform
- Chronic-disease management devices and digital-health apps
Why it matters:
Backed by parent group iFLYTEK, Xunfei benefits from deep capabilities in speech recognition and large-language models. With deployment across 60,000+ primary-care sites and 500+ major hospitals, it is one of the largest-scale medical-AI rollouts in China. Its broad footprint in clinical documentation, decision-support, and telemedicine positions it as key digital infrastructure within primary and community care.
What These Companies Tell Us About China’s AI-Health Trajectory
Across these eight companies, a few patterns stand out:
1. Imaging is the gateway application
Medical imaging remains the fastest path to product-market fit. It’s where data is rich, labels are clear, and clinical value is easy to measure in minutes saved and errors avoided.
2. Data platforms are the new power centres.
Yidu Tech and LinkingMed illustrate that whoever controls the structured, longitudinal, multi-institutional health data can power not just one AI model, but dozens. Perhaps this is where real defensibility lies?
3. Regulatory maturity is catching up.
Approvals such as Deepwise’s breast-cancer device and Infervision’s multi-jurisdictional certifications signal that Chinese AI-health firms are learning to navigate high-bar regulatory regimes, at home and abroad.
4. The frontier is moving from “point tools” to “copilots”.
Several of these companies are already trying to execute system wide models embedded across hospital departments and job functions. The direction of travel is clear: away from single-use tools, toward integrated assistants that sit alongside clinicians and management staff at every step.
Why This Matters Outside China
China is testing AI in healthcare at a scale few other countries can match. The companies above are not redefining medicine everywhere yet, but they are revealing what becomes possible when policymakers, hospital groups, and tech firms are aligned around AI adoption at scale and standardisation into daily clinical workflows.
Whether one sees China as a collaborator, a competitor, or simply a bellwether, its AI-health trajectory offers an early preview of the operational, regulatory, and workforce challenges Western systems will soon face. Understanding this shift now is the first step toward shaping how, and by whom, the next generation of clinical infrastructure is built.