June 26, 2026 — 101 Health Research proudly partnered with the MIMAROPA Health Research and Development Consortium (MHRDC) to host a two-day virtual Seminar-Workshop titled “AI in Health: Advancing Health R&D, Transforming Lives,” held on June 24-25, 2026. This comprehensive training program aimed to equip researchers, clinicians, and academic leaders across the region with the practical skills needed to integrate artificial intelligence and data science into their research methodologies.
The event, hosted via Zoom, featured two primary resource speakers: Dr. Iris Thiele Isip-Tan (Professor and Chair of the Medical Informatics Unit at the UP College of Medicine) led Day 1, while our Founder and Managing Director, Dr. Venus Oliva Cloma-Rosales, MD MPH ME, spearheaded the Day 2 sessions.
Dr. Cloma-Rosales delivered a multifaceted presentation on “AI for Health Systems, Discovery, and Diagnostics,” sharing seven distinct, real-world case studies generated directly from the 101 Health Research portfolio. Her session provided participants with a practical roadmap for moving beyond basic correlations to uncover complex relationships and real-time trends using AI.
Real-World AI Applications: Lessons from the Field
Rather than focusing solely on generative AI as a writing assistant, Dr. Cloma-Rosales challenged participants to view AI as a robust analytical toolkit. She emphasized the critical “AI Problem-Solving Framework,” reminding researchers to always start with the health problem, assess data readiness across five dimensions (Availability, Volume, Quality, Accessibility, and Relevance), and then select the appropriate AI methodology.
Key case studies presented during the session included:
- Big Data in Health Financing: Dr. Cloma-Rosales detailed how 101 Health Research processed over 77 million PhilHealth claims observations (over 80GB of data) to evaluate the All-Case Rates (ACR) policy, ultimately informing the transition to Diagnosis-Related Groups (DRG).
- NLP for Policy Evaluation: By employing Natural Language Processing (NLP) and automated text mining across national databases (like HERDIN, PCHRD, and RDMD), the team mapped research outputs to the National Unified Health Research Agenda (NUHRA), identifying systemic gaps and aligning future R&D investments.
- Automated Encoding for HERDIN: Dr. Cloma-Rosales showcased a patent-pending AI pipeline developed by 101 Health Research that utilizes Optical Character Recognition (OCR) and Large Language Models (LLMs) to automatically extract and index metadata from scanned research documents, drastically reducing manual encoding backlogs for the national health database.
- Precision Medicine via Machine Learning: Utilizing Gaussian Graphical Models (GGM), researchers mapped complex dietary patterns related to endometriosis. Furthermore, by employing K-means cluster analysis on 77 mixed-data variables, the team identified three distinct diabetes phenotypes among young Filipino adults, moving toward highly individualized, precision medicine strategies.
- Computer Vision in Diagnostics: The session concluded with a discussion on how predictive ML models (like Linear Support Vector Machines) can utilize CT imaging and radiomic features to accurately differentiate between tuberculosis and lung cancer.
The AI Use Case Canvas
During the afternoon workshop, participants applied these concepts directly to their own work. Utilizing the AI Use Case Canvas, researchers mapped out specific health challenges, identified available data sources, and proposed relevant AI approaches—from NLP to Big Data Analytics—to generate actionable insights for their respective institutions.
Reflecting on the successful two-day workshop, Dr. Cloma-Rosales emphasized, “Technology should serve the decision, not the other way around. AI is a toolkit, and the right tool, applied to the right problem with the right data, creates impact.”
101 Health Research extends our sincere gratitude to MHRDC and all the participants from various institutions across the MIMAROPA region for their active engagement and commitment to transforming health research.