This paper presents OpenLens AI, a fully automated framework for health informatics research. Health informatics research is characterized by diverse data types, rapid knowledge expansion, and the need for integrated insights across biomedical science, data analytics, and clinical practice. OpenLens AI is designed to address these challenges by integrating specialized agents for literature review, data analysis, code generation, and manuscript preparation, while enhancing visual-linguistic feedback for medical visualization and quality control for reproducibility. Building on recent advances in large-scale language model (LLM)-based agents, it automates the entire research pipeline to generate publishable LaTeX manuscripts with a transparent and traceable workflow. It addresses the challenges of existing systems, which lack the ability to interpret medical visualizations and address domain-specific quality requirements.