ReviewNPJ digital medicine2025
Guiding responsible AI in healthcare in the Philippines.
Review in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- The Incarnate Clinic: Pope Leo XIV's Magnifica Humanitas, AI Optimization, and the Bioethics of Technological Colonialism in Philippine Healthcare.Journal of religion and health · 2026Article
- Algorithmic Moral Burden: Pope Leo XIV, Conscience, and Professional Agency in AI-Supported Philippine Healthcare.Journal of religion and health · 2026Article
- The Patient Beyond the Dataset: Levinas, Magnifica Humanitas, and the Principle of Non-totalization in AI Healthcare in the Philippines.Journal of religion and health · 2026Article
- When AI MeetsJournal of general and family medicine · 2025Article
- AI Literacy in Health-Professions Education: Deepening the Case for Curricular Reform in the Philippines.Health science reports · 2025Article
- Response to "AI Literacy in Health-Professions Education: Deepening the Case for Curricular Reform in the Philippines".Health science reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Philippines faces significant barriers to the safe and effective deployment of AI in healthcare. By leveraging lessons learned from other Southeast Asian nations, the European Union, and the United States, the Philippines can develop a national strategy to deploy AI in healthcare. Drawing from experiences of other nations, we provide considerations, foundational recommendations, and relevant resources to assist leaders in developing and adopting responsible AI in Philippine healthcare.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.