ArticleScientific reports2026
Artificial intelligence enabled performance evaluation of an enhanced SPR biosensor for malaria diagnosis.
Article in Scientific reports, 2026. 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.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Malaria remains a serious global health problem, particularly in areas where drug-resistant Plasmodium species and the expanded geographical distribution of malaria caused by climate change are of concern. In response to the pressing need for a rapid and highly sensitive malaria diagnostic method, this paper proposes a novel surface plasmon resonance (SPR) biosensor design with a multilayer N-FK51a+SiO
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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.