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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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BioKMS-HAG: A hierarchically guided biomedical and space science knowledge fine-grained mining system.

Wenzheng Song¹, Yanzhong Wen¹, Xinyang Yue¹

¹School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China.

Life Sciences in Space Research

|April 29, 2026

Summary

This study introduces the Biomedical Knowledge Mining System (BioKMS) with the Hierarchy Guided Approach (HAG) for AI-driven biomedical hypothesis generation. BioKMS and HAG improve accuracy and efficiency in scientific discovery using biomedical data.

Keywords:

Biomedical knowledge graph Graph neural networks Hypothesis generation Link prediction Software system Space life science

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Published on: February 23, 2019

Area of Science:

Biomedical Informatics
Artificial Intelligence
Space Life Sciences

Background:

Rapid growth in biomedical data and AI present opportunities for scientific discovery.
Accessible tools are needed to integrate advanced AI methods for leveraging this data.

Purpose of the Study:

Develop the Biomedical Knowledge Mining System (BioKMS) integrating knowledge graph construction and link prediction.
Implement the Hierarchy Guided Approach (HAG) for fine-grained biomedical hypothesis generation.
Enhance AI-driven knowledge discovery in biomedical and space life sciences.

Main Methods:

Developed BioKMS, an interactive platform for exploring biomedical and space life science data.
Integrated HAG, a hierarchical tree-guided Graph Neural Network model, into BioKMS for refined link prediction.
Utilized knowledge graph construction and advanced link prediction techniques.

Main Results:

Achieved significant improvements in predictive accuracy, especially for complex biomedical entities.
Demonstrated reduced computational overhead in hypothesis generation.
Enabled seamless knowledge discovery across disciplines.

Conclusions:

The integration of HAG into BioKMS streamlines hypothesis generation and accelerates research efficiency.
This user-friendly system showcases the transformative potential of combining AI methodologies for scientific research.
Paves the way for more efficient biomedical and space science research through advanced AI integration.