Great news
Recently, the 2026 Association for the Advancement of Artificial Intelligence (AAAI), a top-tier international conference in the field of artificial intelligence, has officially announced its paper acceptance results. The Intelligent Healthcare Laboratory of the School of Applied Sciences at the Macao Polytechnic University had a total of four papers accepted by this prestigious CCF-A classified conference, demonstrating strong research capabilities in the interdisciplinary field of artificial intelligence and intelligent healthcare!
Association for the Advancement of Articial Intelligence(AAAI)
AAAI is one of the longest-standing and most authoritative top-tier academic conferences in the field of artificial intelligence, recognized as a CCF-A conference by the China Computer Federation (CCF). The competition for paper acceptance is exceptionally fierce—the 2026 conference received a record 23,680 submissions, of which only 4,167 were selected for presentation, resulting in an overall acceptance rate of just 17.6%.
The four papers of the laboratory focus on the cutting-edge applications in the fields of artificial intelligence, re medical health, 3D modeling and so on. Each paper represents a technological breakthrough in a subdivided field.
The contents of these four papers are as follows.
《LUMIN: A Longitudinal Multi-modal Knowledge Decomposition Network for Predicting Breast Cancer Recurrence》
This paper addresses the clinical challenge of breast cancer recurrence prediction by proposing a Longitudinal Multi-modal Knowledge Disentanglement Network. It effectively integrates patients' multi-temporal data and diverse medical data types (such as medical images, pathological reports, and clinical indicators) to precisely disentangle and synthesize disease knowledge. The framework provides more intelligent decision support for breast cancer recurrence risk assessment, thereby facilitating early clinical intervention.
《HiFi-Mesh: High-Fidelity Efficient 3D Mesh Generation via Compact Autoregressive Dependence》
Targeting the persistent challenge of balancing efficiency and precision in 3D mesh generation, this paper introduces a Compact Auto-regressive Dependency Mechanism. This approach achieves high-fidelity and high-efficiency 3D mesh generation simultaneously. The technology can be widely applied in medical organ reconstruction and virtual reality applications, offering a novel paradigm for 3D digital twin technology.
《EndoIR: Degradation-Agnostic All-in-One Endoscopic Image Restoration via Noise-Aware Routing Diffusion》
Focusing on the critical issue of endoscopic image quality enhancement, this paper proposes a Noise-Aware Routing Diffusion Model that enables degradation-agnostic unified endoscopic image restoration. It adaptively handles various degradation problems in endoscopic images, including blur and noise, providing high-definition visual support for accurate diagnosis of digestive tract diseases. This assists endoscopists in detecting lesions at earlier stages.
Multi directional "continuous deep cultivation" of smart medicine
The laboratory has made synchronous efforts in multiple subdivisions of smart medicine. The fourth paper focuses on the "deep integration of artificial intelligence and medical health" (such as medical data mining, intelligent auxiliary diagnosis and other directions), and continues to expand the technical boundary of smart medicine.
Future work
The Intelligent Healthcare Computing Laboratory at Macao Polytechnic University has been deeply dedicated to the interdisciplinary field of "Artificial Intelligence + Healthcare", adopting a clinically-driven approach to address real-world medical needs. It has consistently pursued breakthroughs in medical image analysis, disease prediction modeling, and innovative AI algorithms for healthcare. The acceptance of four papers at AAAI 2026 not only demonstrates the team's robust research capabilities but also highlights the university's cutting-edge explorations in intelligent healthcare. Moving forward, the laboratory will continue to leverage technological innovation to advance healthcare, facilitating the transition of AI achievements from laboratory research to clinical practice, thereby contributing "Macao's unique expertise" to the evolution of intelligent healthcare.