TIANJIN, China, June 27, 2025 /PRNewswire/ -- From June 24 to 26, the World Economic Forum 2025 Annual Meeting of the New Champions (the 16th Summer Davos Forum) was held in Tianjin. Artificial intelligence, as the new frontier of global economic growth, was one of the hottest topics of this year's forum.

Ms. Gong Rujing (Gong Yingying), Founder and Chairwoman of Yidu Tech, was invited to attend the forum as a representative of the AI healthcare industry and a Young Global Leader. She delivered insightful remarks in the themed dialogue "The AI+ Era", sharing the stage with Dr. Peter Koerte, Member of the Managing Board, Chief Technology Officer and Chief Strategy Officer of Siemens AG; Zhu Min, Senior Fellow at the China Center for International Economic Exchanges and former Deputy Managing Director of the International Monetary Fund; and Kenny Lam, CEO Asia Pacific at Two Sigma. The dialogue was moderated by Azeem Azhar, CEO of Exponential View.

Yidu's Healthcare Innovation Practice: From Data Intelligence Infrastructure to AI Clinical Implementation Gong Rujing (Gong Yingying) pointed out that the trend of population aging poses a severe challenge to healthcare systems: "The original intention of founding Yidu Tech ten years ago was based on the foresight that the traditional healthcare supply chain would be unsustainable under the aging peak expected by 2030." She emphasized that the core prerequisite for the implementation of AI in the medical field is to overcome the challenge of unstructured medical data.

Over the past ten years, Yidu Tech has invested considerable resources in promoting data standardization governance, making it truly computable and applicable. The company's core algorithm engine, YiduCore, has cumulatively and legally processed and analyzed over 6 billion medical records—this is the foundational resource enabling AI technology to deeply empower healthcare.

With the breakthrough progress in large model technology, Yidu Tech's years of medical data governance capabilities are generating exponential value—the company has not only independently developed a large language model in the medical domain but also launched a Clinical-Grade Intelligence Engine "AI Middleware Platform" to drive the construction of smart hospitals, successfully implemented in over 30 well-known top-tier hospitals within three months. "At present, each doctor handles 30 to 100 patient visits per day. The AI Middleware Platform is deeply integrated into the entire diagnosis and treatment process as doctors' 'AI Copilot Station', continuously empowering pre-diagnosis information integration, in-consultation decision support, and post-diagnosis patient management, thereby reducing doctors' burdens." In the pre-diagnosis phase, the intelligent pre-consultation system collects patients' chief complaints, medical history, medication information, etc., through natural language interaction, improving the density of valid information. Particularly noteworthy is the intelligent medical record generation function, which can integrate the patient's pre-consultation information, consultation recording, and historical data (examinations/imaging/past records, etc.) with one click to generate a preliminary medical record, significantly reducing doctors' workload.

In the in-consultation phase, AI can parse patients' past medical records within seconds, dynamically generate a timeline and trend charts of patients' treatment history to help doctors quickly understand key medical history. AI also comprehensively considers diagnostic data and marks the basis for decisions, effectively supporting clinical decision-making while ensuring scientific rigor and reliability.

In the post-diagnosis phase, the AI patient management platform enables data interconnectivity within and outside the hospital. Based on specialized large language models, it provides personalized follow-up, rehabilitation guidance, and medication guidance services to improve patient compliance.

"This not only frees up doctors' time but also significantly improves the quality of diagnosis and treatment and patient experience through precision data-driven methods," said Gong Rujing (Gong Yingying). From February to June 2025, the AI diagnosis and treatment assistant built on the AI Middleware Platform assisted doctors in serving a total of 26,000 patients.

Human-Machine Collaboration: From Medical Empowerment to Organizational Evolution Gong Rujing (Gong Yingying) believes that current AI development is still in its early stage, and its ultimate form has not yet taken shape. Therefore, Yidu Tech maintains an open mindset and takes "creating real value in end-user scenarios" as the core anchor of its AI strategy. She emphasized: "The key to harnessing AI lies not only in the technology itself but also in achieving deep collaboration between humans and technology." This concept is deeply reflected in Yidu Tech's innovation in medical practice. The pain point of traditional AI healthcare lies in the attempt to use standardized tools to meet the diverse needs of doctors. However, uniformly built models or applications cannot meet the stringent requirements of specialists for professional depth, nor can they flexibly adapt to the specific work scenarios of doctors with different levels of seniority and positions. To solve this contradiction, Yidu Tech launched the "Custom Smart Assistant" function on top of the AI Middle Platform, allowing doctors to independently design intelligent assistants tailored to their unique needs through zero-code, "Lego-style" modular construction. This is a key step for AI in healthcare to move toward deeply contextualized scenarios and marks a shift from the previous "tool-based empowerment" to doctor-led "co-creation of capabilities". AI tools developed by doctors themselves will become a key force in enhancing the accessibility of medical services.

At the same time, the concept of human-machine collaboration is also driving the internal organizational evolution of Yidu Tech. "During periods of rapid technological iteration, an organization's learning capacity, resilience to change, and value orientation are more important than a single technological advantage." Gong Rujing (Gong Yingying) actively advocates that the team embrace AI transformation, maintain high adaptability, and form an efficient collaborative working relationship with AI agents. Currently, AI agents have taken on about 20% of Yidu Tech's daily work. This is not only an improvement in efficiency but also a substantive manifestation of the organizational form and work paradigm moving toward "human-machine symbiosis." "Data privacy, cross-institution collaboration, and technological ethics are common challenges faced by AI healthcare development worldwide. However, the large-scale application scenarios of China's healthcare system provide a unique advantage for AI technology iteration." In the global tide of accelerating toward an intelligent era, Gong Rujing (Gong Yingying)'s sharing at the Summer Davos Forum showcased the innovation strength of AI healthcare enterprises and offered a practical path for the industry's development. As "AI + Healthcare" evolves from concept to deep implementation, Yidu Tech will remain grounded in data and empowered by AI, continuously exploring new possibilities and driving the healthcare industry toward greater efficiency, precision, and accessibility.

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