ArticleJournal of public health research2025
AI X-ray for tuberculosis screening in remote Nepal: Benefits and challenges from a doctor's perspective.
Article in Journal of public health research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- 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
Artificial intelligence (AI)-enhanced ultraportable X-ray machines have been recently introduced in our region as tools for community-based pulmonary tuberculosis (TB) screening. Compared to the previously used method of relying solely on "any symptoms of tuberculosis," chest X-ray screening is a more efficient and practical approach. Subclinical TB cases, who often lack overt clinical symptoms, may still be infectious and can present with radiographic abnormalities detectable on chest X-rays. Therefore, a parallel screening strategy combining chest X-rays and symptom assessment, followed by confirmatory sputum testing, is effective in detecting both clinical and subclinical TB cases (with X-ray abnormalities) within the community. The integration of this algorithm, along with AI-assisted portable X-ray devices, represents a significant advancement in community TB screening, although some limitations remain.
Indexed as
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.