The wave of artificial intelligence is sweeping across every industry, but its pace of adoption is uneven. It is notable that while AI has caused significant disruption in fields like poetry, art, and presentation creation over the past two years, one sector has appeared relatively quiet: healthcare. Yet, the healthcare industry is in dire need of AI solutions. The World Health Organization projects a global shortage of 15 million healthcare workers by 2030. To put this number in perspective, it is nearly equivalent to the entire resident population of Shenzhen. A study published in The Lancet provides a more detailed calculation, stating that a minimum of 20.7 doctors per 10,000 people is required to ensure at least 80% of the population has access to medical care. However, in sub-Saharan Africa, this figure is only 2.5 doctors per 10,000 people, just one-eighth of the minimum standard. Even developed nations like the United States face a physician shortage. The Association of American Medical Colleges anticipates a deficit of 124,000 doctors in the U.S. by 2034, where waiting ten months for surgery is commonplace. The challenge lies in balancing the decade-long process of training specialized doctors with the ever-increasing influx of patients. A recent financial report from a leading medical company offers a potential solution.

The recent first-quarter 2026 report from Mindray Medical contains several noteworthy figures that hint at underlying strategic shifts. First, its international business: Mindray's international revenue for the quarter was 4.449 billion yuan, a year-on-year increase of 15.7%, accounting for 53% of the group's total revenue. This growth was broad-based, not reliant on a single market. The European market grew by over 25%, with gains even in challenging markets. Developing countries also performed well, showing a 19% year-on-year revenue increase in U.S. dollar terms. Looking back, the 2025 annual report showed Mindray's international market revenue reached 17.65 billion yuan, up 7.40% year-on-year, with its share of total company revenue rising to 53% for the first time. This proportion places Mindray firmly among the global giants in the medical device industry, comparable to Medtronic, Abbott, and Johnson & Johnson, whose overseas revenue typically ranges between 40% and 60%. This indicates that Mindray's internationalization is no longer driven by individual star products but by the synergistic effect of its entire product portfolio in overseas markets.

A second detail is the dividend. Mindray simultaneously proposed its first interim dividend plan for 2026, offering 12.5 yuan per 10 shares, totaling a distribution of 1.516 billion yuan. This dividend amount represents 65% of the first-quarter net profit attributable to shareholders. A company willing to distribute such a high proportion of earnings in a quarterly report demonstrates extreme confidence in its cash flow management. Historically, from its 2018 listing to the end of 2025, Mindray's cumulative dividends and share repurchases have exceeded 37.3 billion yuan, more than six times its IPO fundraising amount. However, the most critical aspect of this quarterly report lies in a third data point: R&D investment. What is truly significant is where Mindray is allocating its funds. In the first quarter of 2026, Mindray's R&D expenditure reached 889 million yuan, accounting for 10.64% of its operating revenue. Looking back at 2025, despite a complex external environment, R&D investment still amounted to 3.929 billion yuan, maintaining a high proportion of 11.8% of revenue. Since 2018, cumulative R&D investment has surpassed 20 billion yuan. Mindray's R&D intensity and ratio are not only leading among domestic medical device enterprises but also rank high compared to international giants. This substantial investment has enabled products like patient monitors, anesthesia machines, ventilators, and hematology analyzers to secure a position within the top three globally in terms of market share. A more important signal is that Mindray is comprehensively advancing its efforts in AI and digital intelligence.

Mindray's commitment to innovation is reflected not only in R&D spending but also in its exploration of cutting-edge technologies. A prime example is the continuous emergence of AI innovations and integrated solutions, helping the company break into high-end markets. In the in-vitro diagnostics sector, Mindray has developed real-time quality control for patient data based on neural networks. This technology innovatively integrates AI and big data algorithms with traditional real-time quality control to address issues like low sensitivity, frequent false alarms, and difficult parameter selection in conventional models, thereby monitoring system quality in real-time. As a result, the number of samples needed to detect systematic errors is reduced by 67%, and intelligent alarm algorithms cut false alarms to 1/100 of the original level, significantly boosting efficiency and accuracy. In the patient monitoring and life support segment, Mindray has launched the RuiZhi Critical Care Decision Support System, the RuiZhi Perioperative Decision Support System, the RuiZhi Equipment Management Information System, Early Indicator Analysis (EIA) technology, and intelligent ventilation technology, deeply embracing AI. For instance, the clinically validated EIA algorithm provides an average early warning of patient deterioration about 20 minutes in advance, with an identification accuracy exceeding 80%, placing it at the industry's forefront. In medical imaging, Mindray introduced the Nuewa A20 product, offering a full-stack, panoramic intelligent solution for obstetrics and gynecology, utilizing genuinely effective and user-friendly AI to enhance clinical quality and efficiency comprehensively. In obstetrics, for example, AI empowers clinical scenarios covering screening from early to late pregnancy, from routine screening to specialized prenatal diagnosis. In emerging business areas, Mindray is exploring digital-intelligent solutions for animal medical care. For instance, using a cloud-based SaaS model combined with clinical insights, Mindray Animal Medical has developed intelligent auxiliary diagnosis models based on in-vitro diagnostics for specific complex diseases, along with agents, ACE, and knowledge bases for animal-specific diseases, achieving excellent sensitivity, specificity, and accuracy in disease diagnosis.

These explorations are not fleeting initiatives. Public information indicates that since 2015, Mindray has been exploring and attempting to integrate AI with its three main product lines: medical imaging, in-vitro diagnostics, and patient monitoring and life support. A landmark event was the 2024 launch of the Qi Yuan Critical Care Large Model, the world's first clinically implemented large model for critical care medicine, aiding in全面提升ing the precision and quality of diagnosis and treatment. Today, Mindray's Qi Yuan ecosystem is increasingly robust, having released multiple products including the Qi Yuan Critical Care Medicine Large Model, the Qi Yuan Perioperative Medicine Large Model, the Qi Yuan Clinical Engineering Large Model, the Qi Yuan Obstetrics and Gynecology Large Model, and the Qi Yuan Breast Disease Large Model. It is important to note that Mindray's digital-intelligent initiatives are not theoretical but proven in practice. Its overall digital-intelligent solutions have accumulated numerous mature use cases among high-end clients domestically and internationally. These include top-tier institutions such as the U.S. CHS Group (one of the top ten IDNs), St Thomas' Hospital in the UK, Charité – Universitätsmedizin Berlin in Germany, Hôpital de la Pitié-Salpêtrière in France, Hospital Universitario La Paz in Spain, Hospital Israelita Albert Einstein in Latin America, and a number of leading domestic medical institutions. Evidently, as digital-intelligent solutions evolve, they not only address more clinical challenges but also become powerful tools for market expansion. A virtuous cycle is forming: continuous digital-intelligent development solves more clinical problems, leading to greater customer recognition and improved performance, which in turn fuels further R&D and digital-intelligent advancement.

Some may question why Mindray, a company that started by selling monitors and ultrasound systems, is venturing into large models. Why not just focus on hardware? Mindray's Chairman, Li Xiting, addressed this in a previous letter to shareholders. He posed the question to AI: How should the medical device industry evolve in the face of global disparities in medical resources and accelerating aging? The top response from AI was technological innovation and digital intelligence. Underpinning this is healthcare's long-standing "impossible triangle": the simultaneous attainment of high-quality care, high efficiency (speed), and low cost is exceptionally difficult. With aging populations accelerating and chronic disease patients increasing, this supply-demand矛盾 will only intensify. Simply training more doctors cannot close this gap. Technological means are essential to multiply the efficiency of existing medical staff, with AI taking on part of the auxiliary decision-making workload. This is the fundamental logic behind Mindray's bet on digital intelligence—it is driven by genuine need, not simply chasing trends.

Furthermore, examining Mindray's strategy reveals a genuine attempt to solve this "impossible triangle." Consider a specific example: at The First Affiliated Hospital, Zhejiang University School of Medicine, the Qi Yuan Critical Care Large Model can provide an early warning for septic shock up to 6 hours in advance. For a sepsis patient, 6 hours can be the difference between life and death. While issuing the warning, the system automatically captures the patient's key indicators and provides specific treatment recommendations. Additionally, the model can complete medical record writing—a major headache for doctors—in about one minute, increasing efficiency by over 30 times. This means every minute saved for the doctor is returned to the patient. Recently, Mindray's globally first critical care large model was upgraded, adding four key functions: Septic Shock预警, customizable Clinical Decision Support (CDSS), Nursing Decision Support (NDSS), and full-process ECMO treatment management. These seemingly disparate features address a common problem: integrating tasks previously requiring multiple people, multiple systems, and multiple stages into a single intelligent agent. This is highly significant. Previous clinical decision support systems were fragmented—ECG interpretation used one software, blood gas analysis another, and medication dosage calculation yet another. They operated in silos, unable to communicate. It was like a patient consulting three specialists who give uncoordinated advice. The upgraded Qi Yuan Critical Care Large Model integrates condition monitoring, diagnosis and treatment decisions, nursing execution, and specialized therapies. The customizable CDSS feature is particularly clever—hospitals can train the AI according to their own clinical practices. This transforms the AI from a generic tool into a bespoke asset. This represents not just a version update but a leap from an integrated platform for medical-nursing-engineering collaboration towards a multi-collaborative intelligent agent for critical care, marking a significant breakthrough. The Qi Yuan large model family now comprises six members—critical care, perioperative, clinical engineering, laboratory, breast, and obstetrics/gynecology—making it one of the most extensive medical vertical large model systems in China. Through this digital-intelligent system, Mindray is leveraging the "impossible triangle."

Looking deeper, after years of accumulation, Mindray's digital-intelligent strategy has formed a coherent system, internally structured across five layers. The first layer is perfecting each individual product. But Mindray's definition of "perfection" goes beyond marginal improvements in precision. Take ventilators: patients often experience "patient-ventilator asynchrony," where the machine delivers air at a fixed rhythm that conflicts with the patient's own breathing pattern. Mindray's SV70 non-invasive ventilator, through unique hardware platform innovations and integrated turbine sensing technology, achieves a human-ventilator synchrony rate exceeding 90%. Patients using it barely feel the machine's presence, representing a fundamental technological breakthrough. The second layer is device integration. Previously in operating rooms, monitors, anesthesia machines, ultrasound systems, and ventilators operated independently, forcing doctors to constantly shift attention between multiple screens. Device integration links them together for data sharing. An analogy would be replacing a single guard watching four separate doors with one guarding a single, integrated gate, enhancing both efficiency and safety. The third layer is ecosystem building. Integration within one room is insufficient; devices across an entire hospital, or even different hospitals, must communicate in a common language. The RuiZhi Connect platform serves as this backbone, interconnecting devices from different hospitals and geographical locations. Some hospitals in Australia use this system to allow patients in remote areas to receive care without traveling to major cities. The fourth layer is the Qi Yuan large models. This layer addresses the question of "what to do with the data once collected." The first three layers gather and integrate data; the fourth layer transforms this data into actionable clinical decisions. If the first three layers are likened to collecting books from various sources and organizing them on shelves, the Qi Yuan large model is the scholar who has read all the books and can answer any question instantly. The fifth layer is embodied intelligence, equipping AI not just with "eyes" and a "brain" but also with "hands." The ultrasound robot is an example: the AI can autonomously perform the complete loop of probe positioning, image plane acquisition, real-time analysis, and report generation, eliminating the need for manual scanning and waiting for results. Reportedly, Mindray announced its active exploration into the surgical robot business in 2023. Industry sources suggest Mindray's surgical robot targets international top-tier brands, making a strong entry into a market long dominated by the "da Vinci" system.

These five layers represent not simple technological addition but a progression from single-point quality improvement to system synergy, then to data-driven insights, and finally to autonomous AI action. Connecting dots forms lines, connecting lines forms surfaces, gradually creating an ecosystem from which truly disruptive innovations can emerge. The ultimate goal is encapsulated in a statement from Mindray's financial report: to enable devices to achieve genuine autonomy and automation, taking on more repetitive tasks, thereby returning time to doctors and returning doctors to patients. This is not an idealistic slogan. Research tracking Mindray over years shows its products are exported to over 190 countries and regions, covering 87 of the world's top 100 hospitals and the top 30 medical institutions in the U.S. It possesses the industry's most comprehensive product line, with nine product categories holding the number one market share in China and six ranking within the top three globally. Within the Chinese medical sector, Mindray is one of the few players capable of realizing this vision.

In recent years, the tech world has frequently discussed the "singularity"—the point where AI surpasses a critical threshold and enters a phase of explosive growth. While the healthcare industry may be a late adopter, being slow does not mean it will not eventually heat up. Mindray began exploring the integration of AI modules into its products back in 2015—eleven years ago. Essentially, its efforts over this decade have focused on deeply embedding digital-intelligent capabilities into devices, making AI native rather than an add-on. Zooming out, global medical device peers are also racing in this arena. Philips received FDA clearance for the world's first fully AI-powered spectral detector CT; GE Healthcare acquired Intelerad to accelerate its cloud transition; Johnson & Johnson is entering via surgical robots combined with AI pre-operative planning... No one can afford to be slow. Because once a generational gap in AI capability emerges within a product category, it becomes exceedingly difficult for followers to catch up. Mindray's approach is clear: avoid chasing short-term trends and instead systematically embed AI capabilities throughout its entire product ecosystem. A bold prediction is that AI will not remain a supplementary feature; it will gradually become a core competency for medical devices, much like an operating system is essential for smartphones. When these AI-embedded systems are deployed in hospitals, subsequent repurchases, add-on purchases, service upgrades, and software subscriptions will create sustainable revenue streams. Digital intelligence transforms one-time hardware sales into long-term service relationships. Similar to smartphones, the surface transaction is selling a device, but the underlying value lies in selling an ecosystem filled with applications. The value of hardware is fixed, but the value of the ecosystem can grow continuously. According to IDC statistics, the global AI applications market is projected to reach $127 billion by 2025, with the healthcare sector accounting for one-fifth of the total, making it one of the fastest-growing fields in the coming five years. This is the underlying narrative behind the numbers in Mindray's financial report. Revenue and profit are the visible tip of the iceberg. Beneath the surface, the foundation of digital intelligence is growing ever deeper and stronger. In turbulent times, while the surface may be choppy, stability is found in what lies beneath.