Tencent Leads Full-Chain Innovation in Medical AI, 'AI + Healthcare' Boosts Clinical Diagnosis Efficiency
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Tencent's 'MIAI Digital Medical Imaging Platform' has fully opened over 20 medical AI engines to support scientific research and innovation, enabling remote diagnosis, teleconsultation, and assisted diagnosis among other digital imaging applications, driving full-chain innovation in medical AI.
Countries worldwide are actively developing next-generation artificial intelligence, with medical AI advancing rapidly. Tencent has undertaken the construction of the 'National New Generation AI Open Innovation Platform for Medical Imaging' and has successively obtained approvals for innovative medical devices in diseases such as pneumonia, glaucoma, and colon polyps, becoming the first internet technology company to hold multiple Class III certificates for multi-disease and multi-modal medical AI.
AI is being widely applied in clinical disease diagnosis, providing doctors with clinical auxiliary triage suggestions and helping to significantly improve the detection rate of disease screening. According to clinical trials, Tencent MIAI's glaucoma AI engine can reduce the missed diagnosis rate by 20% and the misdiagnosis rate by 2%, while its colon AI engine can help doctors increase the polyp detection rate by over 20%. During the early stages of the pneumonia pandemic, leveraging the advanced algorithms of Tencent YouTu Lab's Tianyan Research Center, the Tencent MIAI team quickly developed a pneumonia AI to assist the imaging department team at Zhongnan Hospital affiliated with Wuhan University, providing lung CT-assisted diagnosis for over 24,000 patients at Leishenshan Hospital.
The widespread adoption of medical AI still faces challenges such as data standardization, supporting applications, and industry-research collaboration. To address these, Tencent has integrated its technological strengths in cloud computing, big data, and user services to launch the 'MIAI Digital Medical Imaging Platform,' focusing on cloud-based digital medical imaging applications, research, and management, deploying AI analysis engines on the cloud to achieve interconnectivity of medical imaging data and business processes.
The 'AI + Healthcare' model holds vast potential in the medical and health industry. Through deep learning algorithms and big data analysis, AI can better assist doctors in accurately diagnosing diseases, providing personalized treatment plans, and offering convenient intelligent assistance during the diagnosis and treatment process. Currently, global tech giants, including Google, Amazon, NVIDIA, Tencent, and JD.com, are racing to deploy 'AI + Healthcare'.
Global Tech Giants Race to Deploy 'AI + Healthcare'
The collision of AI large models is undoubtedly the most eye-catching focus. While improving people's quality of healthy living, innovative applications of AI, big data, and other new technologies in the medical and health industry have also brought significant breakthroughs for industry transformation and upgrading, extending from traditional clinical applications to various endpoints of the industrial chain, such as biopharmaceuticals.
Generative AI is driving innovative transformations in the medical and health industry. While AI-powered large models are deeply integrating with biopharmaceuticals and medical diagnostics, sparking a new wave of artificial intelligence, challenges such as the lack of original algorithms, data privacy protection, and improving diagnostic accuracy remain critical issues to address. AI in healthcare is not a new concept, with previous applications largely focused on medical imaging. However, how AI can closely integrate with complex clinical data has, to some extent, constrained industry development. Now, breakthroughs in AI technology are bringing new possibilities to the healthcare sector.
The rapid development of generative AI is fostering innovative changes in the medical and health industry. AI technologies, represented by large models, are deeply integrating with biopharmaceuticals and medical diagnostics, attracting major tech giants like Google, Amazon, NVIDIA, Tencent, and JD.com to accelerate investments in the "AI + healthcare" field.
Beyond Google, NVIDIA has also been investing in the "AI + healthcare" sector for years. On July 12, NVIDIA invested $50 million in biotech company Recursion to collaborate on the development and training of AI foundation models in biology and chemistry. Following this, Recursion's stock price surged by 78.17%, while NVIDIA's rose by 3.53%.
"AI + Healthcare" Enhances Clinical Diagnosis Efficiency
The "Ruijin on Cloud" smart service and full-process management platform exemplifies this trend. Its multi-campus smart imaging cloud platform, empowered by large models, enables AI-assisted diagnosis for radiology and pathology across multiple disease types, improving clinical efficiency.
The China AI Large Model Map Research Report shows that, as of now, China has released 79 large models with over 1 billion parameters. Applications are rapidly expanding from office, lifestyle, and entertainment sectors to healthcare, industry, and education. At the recent "Boundless Love, Daily Innovation" AI forum in Shanghai, Dimitris Metaxas, a distinguished professor at Rutgers University, noted that medical large models have demonstrated strong capabilities in addressing multimodal data analysis and clinical long-tail problems. For example, in scenarios with limited data, large models can significantly enhance AI performance.
For healthcare processes, SenseTime has developed a smart healthcare platform based on its medical language model "Da Yi." The platform features intelligent triage, pre-diagnosis questionnaires, pre-consultation testing, smart follow-ups, and in-hospital navigation, digitizing and optimizing the entire patient journey from pre- to post-consultation. This reduces patient wait times and improves the overall healthcare experience.
SenseTime's SenseCore infrastructure boasts 5,000 petaflops of computing power, supporting simultaneous training of 20 ultra-large models with hundreds of billions of parameters. Leveraging this computing power and medical foundation models, the company helps healthcare institutions efficiently train models for clinical long-tail problems—individualized and fragmented clinical needs—and even assists them in autonomous model training.
Over the past few years, the development of AI in the medical field has been rapid, bringing revolutionary changes and immense potential to the healthcare industry.
According to McKinsey Consulting data, AI can generate $3.5 trillion to $5.8 trillion in commercial value annually. By 2025, the global AI application market is expected to reach $127 billion, with AI healthcare accounting for one-fifth of the share, indicating a phase of rapid growth.
Renowned market research firm ReportLinker previously predicted in its annual report on the global healthcare AI market that the market size would grow from $14.6 billion in 2023 to $102.7 billion by 2028, with a compound annual growth rate (CAGR) of 47.6% during this period.
China's AI industry has developed rapidly. Since 2019, AI healthcare has grown at a rate of 40% to 60%. The core software market for AI healthcare in China has reached nearly 3 billion yuan, and with the inclusion of capital-intensive AI medical robots, the overall market size approaches 6 billion yuan.
Zhongtai Securities pointed out in a research report that AI+healthcare/pharmaceuticals has vast future potential and is currently worth close attention. The report highlights AI pathology, AI imaging, and AI drug development as promising future application areas.