ArticleCureus2024
Artificial Intelligence for Smoking Cessation in Pregnancy.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Maternal Smoking During Pregnancy and Risk of Autism Spectrum Disorder in Offspring: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2025Review
- Artificial Intelligence in Midwifery: A Scoping Review of Current Applications, Future Prospects, and Midwives' Perspectives.Healthcare (Basel, Switzerland) · 2025Review
- Impact of E-Cigarettes on Fetal and Neonatal Lung Development: The Influence of Oxidative Stress and Inflammation.Antioxidants (Basel, Switzerland) · 2025Review
- Complex interplays: Asthma management and maternal‑fetal outcomes in pregnancy (Review).Experimental and therapeutic medicine · 2024Review
- Tobacco Smoke Exposure and Lactation.Cureus · 2024Review
- 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has emerged as a revolutionary tool in various healthcare domains, including smoking cessation among pregnant women. Smoking during pregnancy is a significant public health concern, linked to adverse maternal and fetal outcomes. Traditional cessation methods have had limited success, necessitating innovative approaches. AI offers personalized interventions, predictive analytics, and real-time support, enhancing the effectiveness of smoking cessation programs. This editorial explores the potential of AI in transforming smoking cessation efforts for pregnant women, highlighting its benefits, challenges, and future prospects. By integrating AI into healthcare strategies, we can improve maternal and fetal health outcomes and contribute to the broader public health goal of reducing smoking rates among expectant mothers.
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.