The 2026 Digital Intelligence in Medicine Conference (CHINC) convened in Beijing from July 3rd to 5th, with the theme "Intelligent Integration in Medicine, Quality Building for Health – New Quality Productive Forces Bolstering Healthy China Construction." The event centered on critical topics such as AI clinical implementation and healthcare data governance. XUNFEIHEALTH (02506) President Tao Xiaodong was invited to deliver a keynote speech at the main forum, where the company officially launched its new-generation AI Diagnosis and Treatment Assistant 2.0.

Furthermore, XUNFEIHEALTH participated extensively in multiple specialized sub-forums covering core areas including medical imaging, primary care diagnosis and treatment, whole-cycle patient management, and clinical application, showcasing its technological depth and large-scale implementation achievements from various perspectives.

Focusing on Four-Tier Innovation and Deepening AI Value Realization in Healthcare

AI in healthcare has now progressed beyond the initial exploration phase, entering a new stage of large-scale and standardized implementation. A series of national top-level policies on "AI + Healthcare" have clearly charted the industry's development direction and practical pathways. In his speech, Tao Xiaodong outlined a four-tier value logic for innovation in the medical field: innovation for its own sake, innovation for doctors, innovation for patients, and innovation for society.

Based on this value framework, XUNFEIHEALTH has established a complete value chain from technology implementation to public health services, contributing to the Healthy China initiative.

Original technological innovation serves as the fundamental bedrock for medical AI to become professional and trustworthy. The extremely high demands of medical scenarios for professionalism, explainability, safety, and compliance mean that general-purpose large models cannot be directly adapted for clinical needs. XUNFEIHEALTH has been consistently building a fully localized, full-stack medical large model foundation.

In June this year, it upgraded and released the Spark Medical Large Model V3.5, achieving breakthroughs in both algorithm and engineering based on fully domestic computing power. This model leads mainstream large models, both domestic and international, in key tasks such as medical Q&A, medical record generation, and multimodal interaction, and is the first in the industry to bring medical record generation and intelligent imaging report generation to a practical threshold, with its medical agent capabilities comprehensively upgraded.

Addressing common industry pain points like model hallucination and unexplainable reasoning, the model constructs dual thinking chains for basic medicine and clinical medicine. The basic medicine chain relies on classic theories of physiology, pathology, and anatomy to trace the underlying logic of diseases and treatments. The clinical medicine chain combines authoritative diagnosis and treatment guidelines with real case data, integrating individual patient information to deduce examination, diagnosis, and prognosis plans, supported by a complete evidence-based traceability system.

The massive volume of real data generated from in-hospital clinical interactions and resident health consultations continuously flows back to iterate the model, forming a virtuous data flywheel. This simultaneously supports the construction of dynamic personal health profiles, providing a reliable technical foundation for personalized healthcare services across all scenarios.

Innovation for Doctors as the Core Driver of AI Clinical Implementation

Centered on the core positioning of "an AI diagnosis and treatment assistant for every doctor," XUNFEIHEALTH translates its technological capabilities into clinical tools covering the entire diagnosis and treatment workflow, directly addressing industry challenges such as heavy documentation burdens, insufficient primary care capabilities, and the limited general practice perspective of specialists. This system has achieved comprehensive coverage from primary care institutions to top-tier tertiary hospitals.

It can provide auxiliary diagnosis and intelligent quality control for over 2,600 diseases, spanning the entire workflow from pre-consultation health record summary generation, in-consultation medical record writing and decision support, to post-consultation follow-up and rehabilitation management. This not only helps free doctors from heavy documentation work, allowing more time for clinical practice, but also standardizes diagnosis and treatment behaviors and narrows the capability gap between different levels of medical institutions through standardized treatment suggestions and quality control mechanisms.

To date, the AI Diagnosis and Treatment Assistant has completed over 1.23 billion auxiliary diagnoses and 580 million instances of assisted medical record writing, serving more than 330,000 doctors and 150 million patients, covering over 420 tertiary hospitals and 77,000 primary care institutions. It has become a core tool for medical institutions at all levels to enhance diagnosis and treatment efficiency and quality.

Innovation for Patients as the Ultimate Goal of Medical AI Services

With the positioning of "an AI health assistant for everyone," XUNFEIHEALTH extends its service boundary from in-hospital diagnosis and treatment to whole-cycle health management outside the hospital, building a three-tier service matrix covering hospital post-discharge care, primary care for chronic diseases, and daily resident health management. This addresses the traditional healthcare system's shortcoming of emphasizing treatment over management.

For discharged patients, it has created an AI post-discharge patient management platform. Based on a "platform + AI + pathway" model, it collaborates with top medical institutions to establish over 150 authoritative disease-specific management pathways, covering about 80% of discharged patients. Through proactive rehabilitation intervention, complication risk warnings, and intelligent follow-up calls, it enables stratified and classified patient management, solving the pain points of lacking post-discharge rehabilitation guidance and low follow-up compliance.

For the general public, with Xunfei Xiaoyi as the core platform, it leverages high-quality in-hospital clinical data and personal health profiles to provide in-depth services such as health record risk warnings, "general practice + specialist MDT" consultations, and whole-cycle health management, allowing people to receive professional health guidance without leaving home.

For communities, relying on the national "AI + Primary Care" pilot base, it has developed a digital intelligent family doctor model, simultaneously improving the work efficiency and service capacity of family doctors. This enables residents to receive continuous, standardized chronic disease management and health services in their local communities, effectively enhancing the accessibility of medical care and health management.

Innovation for Society as the Ultimate Direction of Medical AI Development

XUNFEIHEALTH collaborates with top-tier tertiary hospitals, health departments, and disease control agencies across the country to build a top-tier expert ecosystem, ensuring service professionalism, safety, and compliance from the source. Simultaneously, it has pioneered the connection of data links among primary care institutions, tiered hospitals, and resident health management, breaking down cross-level data barriers and constructing a continuous, dynamic health data system covering the entire population.

By leveraging AI technology to extend high-quality medical resources to underserved areas, it aims to narrow the service capability gap between regions and levels, reducing ineffective treatments and resource waste. Through whole-cycle health management, it moves the disease intervention point forward, lowering the additional medical costs caused by chronic disease progression and complications, thereby potentially reducing overall societal healthcare expenditure at a macro level. This promotes more efficient and equitable distribution of medical resources to benefit all citizens, serving the core goal of improving national health levels.

Introducing the "Super Doctor Assistant": Official Launch of AI Diagnosis and Treatment Assistant 2.0

Based on years of technological accumulation, clinical experience, and continuous focus on the four-tier innovation framework, XUNFEIHEALTH officially launched its new-generation AI Diagnosis and Treatment Assistant 2.0 at the conference. The product represents a generational leap from version 1.0 to 2.0, evolving from a single auxiliary tool into a "Super Doctor Assistant" featuring multi-agent collaboration.

It directly addresses core pain points in advanced clinical scenarios, such as heavy documentation burdens, lagging quality control, limited decision-making perspectives, and insufficient trustworthiness of large models, comprehensively reshaping the human-machine collaborative diagnosis and treatment model.

The Document Generation Agent introduces a new integrated intelligent voice solution with hardware, featuring medically customized microphones. It supports accurate audio capture in noisy environments and multi-speaker voice separation, covering all scenarios from outpatient consultations and ward rounds to surgical notes and discharge summaries. Doctors can dictate to automatically generate standardized medical records.

The Quality Control Agent features a triple-check mechanism based on the thinking chain, building an AI-driven, closed-loop quality control system for the entire process. It can intercept over 60% of medical record quality risks during diagnosis and treatment, establishing a collaborative link between AI, clinical departments, and medical administration to standardize medical record writing from the source.

The Diagnosis and Treatment Decision Agent leverages the comprehensive reasoning capabilities of the Spark Medical Large Model. Combining a patient's real-time condition with historical treatment information, it intelligently suggests potential diagnoses from a general practice perspective, proactively warns of high-risk scenarios like critical illnesses, infectious diseases, and rare diseases, and simultaneously outputs visual diagnostic reasoning paths and references for personalized treatment plans.

The Evidence-Based Support Agent constructs an authoritative medical evidence-based knowledge base, deeply integrating an evidence-based intelligent assistant into the entire diagnosis and treatment chain. It automatically synthesizes multi-dimensional information such as patient signs, test results, and medical history, precisely matching national diagnosis and treatment guidelines and clinical research findings. All AI outputs come with complete traceable evidence, making the reasoning process explainable and verifiable.

Currently, AI Diagnosis and Treatment Assistant 2.0 has completed validation and implementation in several leading tertiary hospitals. In outpatient settings, it has generated over 100,000 medical records with a citation rate of 91%, saving an average of 2.8 hours per doctor per day on documentation. In inpatient settings, the product has been deployed in multiple wards, supporting automatic recording of bedside consultations and one-click referencing at workstations, increasing the efficiency of writing round notes by 98% and discharge summaries by 92%.

As Tao Xiaodong stated in his speech, the new-generation AI Diagnosis and Treatment Assistant 2.0 is not merely a single efficiency tool. It is a full-stack intelligent solution rooted in the four-tier innovation framework and covering the entire medical landscape, aiming to answer the industry's core question: "How can AI deeply integrate into the entire diagnosis and treatment workflow and genuinely empower the improvement of healthcare quality?"

Empowered by AI technology's comprehensive application in the medical field, healthcare services will break free from the limitations of traditional, fragmented information systems, building a more efficient, precise, and compassionate intelligent service system. This represents both the practical results delivered by XUNFEIHEALTH's deep commitment to AI in healthcare and a new starting point for leveraging new quality productive forces to support the Healthy China initiative.