BRAINAURORA-B (06681) has announced that the group has achieved significant breakthroughs across multiple areas recently, with the relevant details now disclosed as follows.
The finals of the 2026 Yiong'an International Healthcare Technology Application Competition were recently held in the Yiong'an New Area. Organized by the Yiong'an Future City Scenarios Hub Committee and themed "Digital Intelligence, Healthy Future," the competition featured three main tracks: Health Big Data Application Technology, Smart Hospital New Scenarios, and Innovative Development of Traditional Chinese Medicine. It attracted 514 institutions and 666 projects from around the world. After multiple rounds of selection, 173 projects advanced to the finals. The group's entry, titled "Application of a Digital Diagnosis and Treatment Platform for Cognitive Disorders Based on Large Models in the Medical Field," competed in the Smart Hospital New Scenarios track against 40 other teams, including those from Tsinghua University, Peking University, Beijing Tongren Hospital affiliated with Capital Medical University, and Hebei Medical University. It ultimately secured first place, earning the championship title.
This award carries significant weight. The competition, supported by national-level industry associations such as the Chinese Medical Association, the Chinese Preventive Medicine Association, the China Association of Medical Equipment, and the China Information Association of Traditional Chinese Medicine, is a highly influential national-level event in the healthcare sector. The group's victory, emerging as the champion from a vast pool of projects, fully demonstrates its technological leadership and industry recognition in the fields of digital healthcare and AI medicine.
In the first half of 2026, the group achieved a series of important scientific research outcomes at the intersection of brain science and AI medicine, with multiple studies published consecutively in top-tier international academic journals.
On June 23, 2026, research findings from a study with deep participation and support from the group's scientific team, in collaboration with Professor Ma Changsheng's team from Beijing Anzhen Hospital, Capital Medical University, and Professor Wang Jiguang's team from Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine, were published online in the authoritative international neuroimaging journal Brain Research. This study utilized advanced 7T ultra-high-field magnetic resonance imaging technology to finely delineate, for the first time, the microstructural and functional abnormalities in the attention network of hypertensive patients with cognitive impairment. It revealed how blood pressure fluctuations, particularly increased pulse pressure, "slow down" thinking speed by affecting specific brain regions. This research not only provides a new perspective for understanding early cognitive decline related to hypertension but also lays a scientific foundation for developing more precise early warning and intervention strategies.
Specifically, the study stemmed from a randomized controlled trial involving 41 hypertensive patients with cognitive impairment. Using 7T ultra-high-field MRI, it systematically analyzed the associations among overall and domain-specific cognitive dysfunction, neuroimaging metrics, and blood pressure. The findings showed that structural atrophy related to cognitive impairment was localized in brain regions overlapping with the attention network. Functional abnormalities, both at the whole-brain level and within the attention network, were associated with worse overall cognitive performance. Notably, intra-network functional hyperconnectivity in key hub nodes of the attention network—the right anterior insula and the right posterior intraparietal sulcus—was significantly correlated with slower processing speed in hypertensive patients and mediated the relationship between pulse pressure and processing speed. These findings offer new insights into the neuropathophysiological mechanisms of hypertension-related cognitive impairment and suggest potential network-based intervention targets.
Another study published in the international cardiology journal Heart on May 14, 2026, was a multicenter randomized controlled trial involving 8 centers in China and 224 patients. It compared the effects of the multi-domain cognitive training provided by the company versus single-domain training in patients with coronary heart disease combined with mild cognitive impairment. The primary endpoint was the proportion of patients with improved cognitive function at 12 weeks, with secondary endpoints including quality of life and adherence. The results showed: 1) No significant difference in the proportion of cognitive function improvement at 12 weeks between the two groups (p=0.947, OR=1.02, 95% CI 0.51 to 2.05), but both were significantly better than baseline (p=0.015 and p=0.016); 2) The multi-domain group had significantly better adherence (p=0.009); 3) The multi-domain group showed significantly greater improvement in quality of life compared to the traditional group; 4) The multi-domain group demonstrated significantly greater increases in gray matter volume in the left supplementary motor area, right precuneus, and right superior parietal lobule compared to the traditional group (Pfamily-wise error=0.004).
The conclusion is that the multi-domain cognitive training regimen demonstrates unique comprehensive advantages in improving treatment adherence, enhancing quality of life, and promoting brain plasticity. These findings not only open a new path for comprehensive rehabilitation in coronary heart disease but also signify that the value of cognitive digital therapeutics in the cardiovascular field has received high-level recognition from the international academic community.
A paper by the group's technical team, titled "Dual-Enhancement Product Bundling: Bridging Interactive Graph and Large Language Model," was accepted by the international journal Electronics. Group CEO Cai Longjun and Algorithm Director Wang Peng served as co-corresponding authors and were awarded the "Best Researcher Award." This research is the first to propose a large model dual-enhancement training framework that combines interactive graph knowledge with large language model semantic understanding for bundle task recommendation. The proposed Dynamic Concept Binding Mechanism effectively alleviates the cold-start problem. This method consistently outperformed all benchmark methods across three public datasets, achieving relative improvements of 6.3% to 26.5%, making a valuable contribution to the advancement and research of large language models in reasoning system applications.
Core Competitive Advantages Reinforced
This championship win and the release of this series of research outcomes further solidify the group's leading edge in digital therapeutics for cognitive disorders and the brain science AI field.
1. Research and Development Capabilities Gain High-Level International Recognition
Consecutive publications in authoritative journals such as Brain Research, Heart, and Electronics mark the group's scientific research level as having reached the international forefront.
2. Industry-University-Research-Hospital Integration Model Proves Highly Effective
Multiple studies involved deep collaboration with top clinical institutions like Beijing Anzhen Hospital, validating the feasibility of the "clinical demand - technology R&D - clinical validation" pathway.
3. Value of Digital Therapeutics in Cardiovascular Field Supported by High-Level Evidence
The randomized controlled trial confirmed that, based on reliable core efficacy, cognitive digital therapeutics can significantly improve adherence and promote brain structural remodeling, providing a new tool for the full-course management of cardiovascular diseases.
4. Application of AI Large Models in the Medical Vertical Field Continues to Deepen
The breakthrough in the dual-enhancement method for large language models and the championship-winning project indicate that the group is at the forefront of the industry in integrating large language models with medical scenarios.
The Board of Directors believes that the aforementioned achievements align with the group's long-term development strategy and will create long-term value for shareholders.
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