The 12th International Conference on Fuzzy Systems and Data Mining (FSDM 2026)

Abstract: The digital transformation of decentralized healthcare demands integrated multi-omics datasets, population health records and translational evidence to support primary care clinical decisions. However, fragmented biological databases and disconnected analytical pipelines create major barriers to translating aging research into real-world healthcare practice. To tackle this challenge, we built AI-Aging, a unified AI-based digital infrastructure delivering an end-to-end translational pipeline spanning multi-omics profiling to population-wide aging health management. The system consists of four standardized, interoperable sub-platforms: HALDxAI, a large-scale aging knowledge graph containing 2.8 million biological nodes and 180 million relational links to dissect aging mechanisms; ARIES, a literature-derived evidence graph enabling traceable causal connections between geroprotective chemicals, molecular pathways and aging phenotypes; AITED, a translational database curating more than 8,700 aging interventions to measure translational gaps and safety signals for clinical trial design; and Fluxera, an interpretable predictive model trained on a cohort of 178,000 participants to map population aging trajectories and forecast individual health risks. Uniform data schemas, open APIs and traceable evidence chains are implemented across all modules, forming a closed-loop system for omics fusion, mechanistic interpretation, intervention assessment and population health forecasting. This infrastructure connects fundamental multi-omics findings with on-the-ground decentralized primary care, establishing a solid digital framework for precision aging intervention and equalized longevity health management.

Keywords: digital health transformation; multi-omics integration; AI knowledge graph; longitudinal health trajectory; ageing translational database; decentralized primary care; longevity research

Biography: Prof. Ming Chen is the director of the Bioinformatics Laboratory at the College of Life Sciences, and is the leading figure in the field of Bioinformatics at Zhejiang University, China. He obtained his Ph.D. in Bioinformatics from Bielefeld University, Germany, in 2004. He was seconded to the Fundamental Research Department of the Ministry of Science and Technology, served as the president's assistant and was specially appointed dean at Inner Mongolia Minzu University. Prof. Chen's research work covers bioinformatics, systems biology, non-coding RNA transcriptomics, and precision medicine. He has published over 200 academic papers in peer-reviewed journals such as Cell, Nature, Nucleic Acids Research, Bioinformatics, etc. with his Google Scholar H-index over 59. He has been included in the list of top 2% scientists of the world.