Collaboration
Collaborate With Us
Computational Integrative Medicine advances through collaboration. We work with hospitals, universities, research institutions, and data organizations worldwide.
Why Collaboration
An Interdisciplinary Endeavor
The challenges CIM addresses cannot be solved by any single institution, discipline, or geography. Advancing the field requires shared methodology, shared data infrastructure, joint research programs, and cross-institutional validation.
We are building the methodological foundations, computational infrastructure, and research programs. But the field itself can only grow through broad collaboration — bringing together clinical expertise, computational methods, longitudinal data, and diverse perspectives.
Partners
Who We Work With
Hospitals & Clinical Institutions
Clinical environments where longitudinal health management is practiced and real-world data is generated. We collaborate on deploying AEGIS infrastructure, co-designing longitudinal studies, and generating evidence from clinical practice.
Universities & Research Institutions
Academic partners in methodology development, computational modeling, data science, and health research. We collaborate on joint research programs, methodology co-development, and shared publications.
Research Organizations
Institutions focused on specific health domains — neurodevelopment, metabolic health, chronic disease management. We collaborate on domain-specific research programs using the CIM methodology framework.
Technology & Data Partners
Organizations working on data infrastructure, knowledge engineering, computational modeling, or AI in health contexts. We collaborate on technical integration, data sharing, and infrastructure development.
Models
How We Collaborate
Research Partnership
Joint design and execution of longitudinal research studies using the CIM methodology framework. Partners contribute domain expertise, clinical access, or data; we contribute methodology, infrastructure, and computational modeling capabilities.
Methodology Co-development
Collaborative development and validation of CIM methodology components — data structure standards, ontology development, modeling approaches, evidence generation methods. Particularly suited for academic partners.
Clinical Collaboration
Deployment of AEGIS infrastructure in clinical settings for longitudinal health management. Clinical partners provide the care environment; AEGIS provides systematic data collection, structured management, and evidence generation.
Data Collaboration
Structured data sharing for research, cross-institutional trajectory analysis, and evidence synthesis. Governed by clear data agreements designed to protect privacy while enabling population-level insights.
Contact
Start a Conversation
If you are working on complex health challenges, longitudinal health data, computational health modeling, or real-world evidence generation, we would welcome a conversation about potential collaboration.
Email: contact@icimresearch.org