ReviewFrontiers in public health2022
On AI Approaches for Promoting Maternal and Neonatal Health in Low Resource Settings: A Review.
Review in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed, 58 citations in OpenAlex.
- Article
- Development and Evaluation of an Adaptive Penguin-Improved LSTM Model Integrating Natural Language Processing for Early Prediction of Pregnancy Syndrome Risks.Birth defects research · 2026Observational
- AI-powered population-based birth cohort study in the Western Province of Sri Lanka: study protocol.BMC pregnancy and childbirth · 2026Article
- Adverse Maternal and Neonatal Outcomes Among Women of Advanced Maternal Age in a Tertiary-Care Setting in Bangladesh: A Cross-Sectional Study.Health science reports · 2026Article
- AI in Childbirth and Emerging Alternatives to Traditional Fertility Treatments.Reproductive sciences (Thousand Oaks, Calif.) · 2026Review
- Using artificial intelligence as a technological tool in gynecologic and obstetric health: A narrative literature review.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026Review
- Artificial intelligence for predicting and preventing adverse pregnancy outcomes addressing bias and clinical translation.Frontiers in digital health · 2026Review
- Artificial intelligence and the future of maternal and newborn health in low-income countries: advancing equity, early detection, and health system resilience.Frontiers in public health · 2026Review
- Expert consensus on pre-eclampsia risk screening tools for low- and middle-income countries: Development of a new Target Product Profile.PLOS global public health · 2026Article
- Real-time quality feedback on Doppler data for community midwives using edge-AI.Machine learning. Health · 2025Article
- The Effectiveness of an Artificial Intelligence-Based Gamified Intervention for Improving Maternal Health Outcomes Among Refugees and Underserved Women in Lebanon: Community Interventional Trial.JMIR mHealth and uHealth · 2025Article
- Strengthening ethics review of the development of artificial intelligence (AI) systems in health research: a guide for research ethics committees in Uganda.BMC medical ethics · 2025Article
- Can AI Bridge or Widen Maternal Health Inequities?Public health challenges · 2025Article
- Article
- Integrating Artificial Intelligence into Perinatal Care Pathways: A Scoping Review of Reviews of Applications, Outcomes, and Equity.Nursing reports (Pavia, Italy) · 2025Review
- The impact of artificial intelligence (AI) on maternal mortality: evidence from global, developed and developing countries.Globalization and health · 2025Article
- Perinatal mental health care goes digital: Opportunities for digital health to revolutionize the care delivery for healthier pregnancies and outcomes.PLOS digital health · 2025Article
- An efficient interpretable framework for unsupervised low, very low and extreme birth weight detection.PloS one · 2025Article
- Evaluating the impact of engaging healthcare providers in an AI-based gamified mHealth intervention for improving maternal health outcomes among disadvantaged pregnant women in Lebanon.Frontiers in digital health · 2025Article
- Pre‑partum blood leukocyte profiles distinguish gestational inflammatory stages that predict birth‑related adverse outcomes.Frontiers in immunology · 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
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A significant challenge for hospitals and medical practitioners in low- and middle-income nations is the lack of sufficient health care facilities for timely medical diagnosis of chronic and deadly diseases. Particularly, maternal and neonatal morbidity due to various non-communicable and nutrition related diseases is a serious public health issue that leads to several deaths every year. These diseases affecting either mother or child can be hospital-acquired, contracted during pregnancy or delivery, postpartum and even during child growth and development. Many of these conditions are challenging to detect at their early stages, which puts the patient at risk of developing severe conditions over time. Therefore, there is a need for early screening, detection and diagnosis, which could reduce maternal and neonatal mortality. With the advent of Artificial Intelligence (AI), digital technologies have emerged as practical assistive tools in different healthcare sectors but are still in their nascent stages when applied to maternal and neonatal health. This review article presents an in-depth examination of digital solutions proposed for maternal and neonatal healthcare in low resource settings and discusses the open problems as well as future research directions.
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.