Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.9K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating bias in target trial emulation for heart failure across statistical and deep learning methods.

Nature communications·2026
Same author

Attitudes to mandatory COVID-19 vaccination in early life: findings from the multi-country cross-sectional CANDOUR study.

Health promotion international·2026
Same author

Big Data and Trustworthy AI for Heart Failure: A Review.

Circulation. Heart failure·2026
Same author

Optimising rapid prenatal exome sequencing in the NHS genomic medicine service: the EXPRESS Synopsis.

Health and social care delivery research·2026
Same author

Eclampsia Incidence, Management and Outcomes Across Multi-Country Surveillance Cohorts: Individual Participant Data Meta-Analysis.

BJOG : an international journal of obstetrics and gynaecology·2026
Same author

Subtyping Alzheimer's disease and Parkinson's disease using longitudinal electronic health records.

Nature aging·2026

Related Experiment Video

Updated: Oct 20, 2025

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
09:24

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable

Published on: May 17, 2024

1.7K

Perinatal health predictors using artificial intelligence: A review.

Rema Ramakrishnan1, Shishir Rao2, Jian-Rong He3,4

  • 1National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Women'S Health (London, England)
|September 14, 2021
PubMed
Summary

Artificial intelligence (AI) offers new ways to improve maternal and infant health outcomes. By leveraging AI for prediction and monitoring, we can enhance perinatal care and reduce health disparities.

Keywords:
artificial intelligencelow birthweightmachine learningperinatal healthpreterm birthsevere maternal morbidity

More Related Videos

Author Spotlight: Assessing the Feasibility of Using Amplitude-Integrated EEG During Neonatal Transport
05:15

Author Spotlight: Assessing the Feasibility of Using Amplitude-Integrated EEG During Neonatal Transport

Published on: June 21, 2024

927
Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
19:15

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

Published on: August 25, 2014

86.7K

Related Experiment Videos

Last Updated: Oct 20, 2025

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
09:24

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable

Published on: May 17, 2024

1.7K
Author Spotlight: Assessing the Feasibility of Using Amplitude-Integrated EEG During Neonatal Transport
05:15

Author Spotlight: Assessing the Feasibility of Using Amplitude-Integrated EEG During Neonatal Transport

Published on: June 21, 2024

927
Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
19:15

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

Published on: August 25, 2014

86.7K

Area of Science:

  • Perinatal Health
  • Medical Artificial Intelligence
  • Public Health

Background:

  • Public health advances have improved pregnancy and birth outcomes, yet significant disparities persist.
  • Perinatal health indicators like maternal mortality and preterm birth remain public health concerns.
  • Artificial intelligence (AI) presents novel approaches for prediction, diagnosis, and monitoring in perinatal health.

Purpose of the Study:

  • To explore the potential of artificial intelligence in improving perinatal health research and clinical practice.
  • To outline key goals for developing and implementing AI in the perinatal field.
  • To foster a multidisciplinary approach for advancing AI tools in perinatal care.

Main Methods:

  • Utilizing machine learning (a type of AI) for predicting outcomes like preterm birth, preeclampsia, and postpartum depression.
  • Applying real-time electronic health recording and AI-driven predictive modeling for fetal and maternal monitoring.
  • Exploring AI for prenatal diagnosis of birth defects and improving assisted reproductive technology outcomes.

Main Results:

  • AI, particularly machine learning, has shown success in predicting various perinatal conditions and monitoring high-risk pregnancies.
  • AI tools are being developed for real-time monitoring, especially in low-resource settings.
  • AI methodologies show promise in enhancing prenatal diagnosis and assisted reproductive technology.

Conclusions:

  • Achieving optimal perinatal health requires population-representative data, adapted AI algorithms, and interpretable AI models.
  • A multidisciplinary approach is crucial for developing trustworthy AI tools in perinatal health.
  • AI has the potential to significantly advance perinatal research, clinical practice, and public health policies.