ArticleProceedings of the National Academy of Sciences of the United States of America2025
Real-world implementation of a noninvasive, AI-augmented, anemia-screening smartphone app and personalization for hemoglobin level self-monitoring.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Feasibility of a Noncontact Photoplethysmography-Based Mobile App for Noninvasive Hemoglobin Monitoring: Exploratory Observational Study.JMIR formative research · 2026Observational
- Anemia in young women: determinants and artificial intelligence-based management approaches.Frontiers in artificial intelligence · 2026Review
- AI supported diagnostic innovations for impact in global women's health.BMJ (Clinical research ed.) · 2025Article
- Real-world implementation of a noninvasive, AI-augmented, anemia-screening smartphone app and personalization for hemoglobin level self-monitoring.Proceedings of the National Academy of Sciences of the United States of America · 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
9 authors.
Funding
Abstract
Anemia, characterized by low blood hemoglobin (Hgb) levels, afflicts >2 billion individuals worldwide. Here, we report real-world data generated by a smartphone app that noninvasively screens for anemia using only "fingernail selfies." App data for anemia screening were obtained from >1.4 million uses across the United States enabling geographic mapping of Hgb levels. Of those, 9,061 users also self-reported complete blood count Hgb levels for comparison, resulting in accuracy and performance that match gold standard laboratory testing and a sensitivity and specificity of 89% and 93%, respectively, when using an anemia cutoff of 12.5 g/dL. Geotagged data enabled construction of an "anemia map" of the United States, which demonstrated that Hgb levels correlate with socioeconomic status, and that the app is more likely to be used in counties with higher median income counties, more Black residents, and more primary care physicians. In addition, "personalization" of the app's AI-augmented algorithm empowers self-monitoring of Hgb levels for those already diagnosed with anemia, such as chronic kidney disease (CKD) patients. After personalization, the app's mean absolute error improved from 1.36 to 0.74 g/dL (
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.