Improving primary healthcare with generative AI.

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

5 citing papers in PubMed.

1. AI knowledge, attitudes, perceptions, and willingness to use AI among oncologists in China: a nationwide cross-sectional study.BMC medical education · 2026
   Article
2. Personalised health plan development using agentic AI in Singapore's national preventive care programme: a pilot study.NPJ digital medicine · 2026
   Article
3. DermaGPT a federated multimodal framework with a meta learned trust function for interpretable dermatology diagnostics.Scientific reports · 2026
   Article
4. Quality safety and disparity of an AI chatbot in managing chronic diseases: simulated patient experiments.NPJ digital medicine · 2025
   Article
5. Opportunities and Challenges for Large Language Models in Primary Health Care.Journal of primary care & community health
   Review

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

Authors and funding

1 author.

Funding

No grant is acknowledged in the PubMed record.

Abstract

PubMed holds no abstract for this paper.