AI & Health Resilience
Healthcare, public health, disaster preparedness and response, and climate and community resilience.
West Visayas State University · AI Research Laboratory
Turning data into evidence for Western Visayas.
iDx is the AI research laboratory of WVSU CICT, applying artificial intelligence and data science to problems in health, agriculture, and enterprise across Western Visayas.
Contact us for collaboration →RESEARCH PROGRAM MAP / 3 DOMAINS · 6 METHODS
3 core research domains
6 research methods
6 research methods
THE LAB
Where computation meets community.
iDx — Intelligence & Data Transformation — exists to make artificial intelligence useful, trustworthy, and locally grounded. We pair machine learning, predictive analytics, and data governance from CICT with domain expertise in health, agriculture, biology, and business — so research findings translate into decisions people can act on.
CORE RESEARCH AREAS
Three domains, one method.
iDx concentrates its work in three applied areas where AI and data transformation create the most immediate value for the region.
AI Agriculture & Food Systems
Precision agriculture, crop and farm monitoring, agricultural decision support, and food security.
AI MSME Innovation
Business intelligence, process automation, and digital transformation for micro, small and medium enterprises (MSMEs).
RESEARCH METHODS
Methods made visible.
These are the analytical techniques applied across the laboratory's research program, spanning predictive modeling, geospatial analysis, applied machine learning, computational network methods, time-series forecasting, and analytics dashboards.
Predictive & Decision-Support Modeling
Statistical and machine-learning models that support decision-making in healthcare, agriculture, and enterprise settings.
Geospatial & Remote-Sensing Analysis
Spatial and remote-sensing techniques applied to climate, agricultural, and disaster-resilience research.
Applied Machine Learning & Data Governance
Machine-learning pipelines developed alongside responsible data-governance practices.
Computational & Network-Based Methods
Graph-based and reproducible computational methods supporting evaluation and analysis across projects.
Time-Series & Forecasting Analysis
Longitudinal and time-series models used to forecast trends in health indicators, crop yields, and enterprise performance.
Business Intelligence & Analytics Dashboards
Interactive dashboards and data-visualization tools that support enterprise decision-making and monitoring.
OUR APPROACH
Principles that guide our research.
Every iDx project moves from question to evidence through the same discipline: rigorous methods, responsible data practice, and close collaboration with domain partners who understand the problem on the ground.
Methodological rigor
Transparent evaluation and reproducible methods across every study.
→Responsible data practice
Ethics and data governance as a starting requirement, not an afterthought.
→Collaboration with domain partners
Government, health, agricultural, and enterprise stakeholders shape our research questions.
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