ReviewFrontiers in artificial intelligence2026
Anemia in young women: determinants and artificial intelligence-based management approaches.
Review in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Anemia is a serious global public health problem, worldwide majority of the young women are suffering with this anemia. Anemia condition is characterized by the deficiency iron, folic acid and other nutrients. Not only nutritional deficiencies, some other factors like environmental, genetic, physiological, nutritional, urbanization and socioeconomic factors influencing the anemia condition. Anemia is highly prevalent and has significant health and economic consequences efforts to decrease its prevalence in this young women group have been surprisingly slow. An Artificial Intelligence helps to shift in addressing the anemic problem. This review focusing on the multifactorial causes of anemia in young women and also AI- based interventions for screening, risk assessment, personalized nutritional counseling, treatment, management and also public health monitoring. AI facilitates greater accessibility, and personalized treatment, its responsible application requires careful consideration of algorithmic biases, data quality, ethical, and seamless integration with current healthcare systems. AI has the potential to revolutionize anemia management and promote equitable responsible and effective health outcomes for young women worldwide.
Indexed as
Identifiers
What Socratic 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 Socratic graph.