Sunday, August 17, 2025
Science
No Result
View All Result
  • Login
  • HOME
  • SCIENCE NEWS
  • CONTACT US
  • HOME
  • SCIENCE NEWS
  • CONTACT US
No Result
View All Result
Scienmag
No Result
View All Result
Home Science News Medicine

Machine learning for maternal health: University of Oklahoma engineer receives NSF Career Award for preeclampsia study

May 6, 2024
in Medicine
Reading Time: 3 mins read
0
Talayeh Razzaghi, Ph.D.
65
SHARES
595
VIEWS
Share on FacebookShare on Twitter
ADVERTISEMENT

Norman, OK – Talayeh Razzaghi, an assistant professor of industrial and systems engineering at the University of Oklahoma, has been awarded a Faculty Early Career Development Program award from the National Science Foundation for her work titled “Personalized Maternal Care Decision Support System for Underserved Populations.”

Talayeh Razzaghi, Ph.D.

Credit: University of Oklahoma

ADVERTISEMENT

Norman, OK – Talayeh Razzaghi, an assistant professor of industrial and systems engineering at the University of Oklahoma, has been awarded a Faculty Early Career Development Program award from the National Science Foundation for her work titled “Personalized Maternal Care Decision Support System for Underserved Populations.”

Known as a CAREER award, Razzaghi was awarded $496,732 to research machine learning-based clinical decision support tools for early preeclampsia detection in maternal healthcare research.

Preeclampsia, a pregnancy complication characterized by high blood pressure, affects 8-10% of pregnancies in the United States annually and poses significant risks to maternal and neonatal health if left untreated. Despite its prevalence, identifying women at higher risk of developing preeclampsia remains challenging due to various contributing factors, including age, race and pre-pregnancy health conditions.

“Our research will address these challenges head-on by using cutting-edge machine learning algorithms to analyze diverse datasets and predict the likelihood of preeclampsia during pregnancy, particularly among underserved minority populations,” Razzaghi said. “The research will focus on mitigating biases inherent in existing predictive models, which often overlook the unique healthcare needs of communities of color.”

Razzaghi adds that the staggering rise in maternal mortality rates in the U.S. over the past two decades demands action. “Through our research, we aim to harness the power of machine learning to provide personalized, equitable maternal care and reduce disparities in maternal health outcomes.”

The approach includes the development of machine learning-based predictive models that are scalable for learning from large-scale healthcare data and yield fair classifiers that balance accuracy and fairness across racial subpopulations. By tackling these technical challenges, Razzaghi hopes to enhance the identification of pregnant women at high risk of preeclampsia while promoting fairness in maternal health management systems.

“This research has far-reaching implications beyond preeclampsia detection,” Razzaghi said. “By understanding and addressing the complex interplay of social determinants of health, we can apply these insights to other pregnancy-related diseases and even non-clinical factors such as socioeconomic status.” She adds that her CAREER award also will focus on a recruitment and research internship program that involves the inclusion of underrepresented students in STEM fields.

Collaborating with clinical partners at the OU Health Sciences Center, Texas Tech Health Sciences Center and the University of Pittsburgh, Razzaghi has access to diverse datasets crucial for training and validating the machine learning models. However, she acknowledges the challenges of accessing sensitive healthcare data and emphasizes the importance of responsible data usage and privacy protection.

“We are committed to upholding the highest standards of data ethics and privacy throughout this research,” Razzaghi said. “Our goal is to advance scientific knowledge and improve healthcare outcomes while respecting the privacy and confidentiality of patient information.”

Learn more about Razzaghi’s research.

###

About the Project:

The project, titled “Personalized Maternal Care Decision Support System for Underserved Populations,” begins Aug. 1, 2024, with funding expected through July 31, 2029. The project is funded by the Info Integration and Informatics Program in the National Science Foundation as part of award #2339992

About the University of Oklahoma:

Founded in 1890, the University of Oklahoma is a public research university in Norman, Oklahoma. As the state’s flagship university, OU serves the educational, cultural, economic and health care needs of the state, region and nation. OU was named the state’s highest-ranking university in U.S. News & World Report’s most recent Best Colleges list. For more information, visit ou.edu.



Share26Tweet16
Previous Post

Grief, unity, and resilience: the impact of memorial days – new study

Next Post

Nanoparticle catalysts convert carbon dioxide to carbon monoxide to make useful compounds

Related Posts

blank
Medicine

New Metabolic Inflammation Model Explains Teen Reproductive Issues

August 17, 2025
blank
Medicine

Mpox Virus Impact in SIVmac239-Infected Macaques

August 17, 2025
blank
Medicine

Epigenetic Mechanisms Shaping Thyroid Cancer Therapy

August 17, 2025
blank
Medicine

Genkwanin Glycosides Boost Glucose Uptake in Fat

August 16, 2025
blank
Medicine

Biosilica Nanoparticles Combat Liver Ischemia Injury

August 16, 2025
blank
Medicine

Treg Therapy Boosts Pro-Inflammatory Th17 via IL-2

August 16, 2025
Next Post
Beta phase molybdenum carbide (β-Mo2C) nanoparticles demonstrate increased catalytic activity in the reverse water gas shift (RWGS) reaction when embedded on a silicon dioxide (SiO2) support structure.

Nanoparticle catalysts convert carbon dioxide to carbon monoxide to make useful compounds

  • Mothers who receive childcare support from maternal grandparents show more parental warmth, finds NTU Singapore study

    Mothers who receive childcare support from maternal grandparents show more parental warmth, finds NTU Singapore study

    27535 shares
    Share 11011 Tweet 6882
  • University of Seville Breaks 120-Year-Old Mystery, Revises a Key Einstein Concept

    948 shares
    Share 379 Tweet 237
  • Bee body mass, pathogens and local climate influence heat tolerance

    641 shares
    Share 256 Tweet 160
  • Researchers record first-ever images and data of a shark experiencing a boat strike

    507 shares
    Share 203 Tweet 127
  • Warm seawater speeding up melting of ‘Doomsday Glacier,’ scientists warn

    311 shares
    Share 124 Tweet 78
Science

Embark on a thrilling journey of discovery with Scienmag.com—your ultimate source for cutting-edge breakthroughs. Immerse yourself in a world where curiosity knows no limits and tomorrow’s possibilities become today’s reality!

RECENT NEWS

  • New Metabolic Inflammation Model Explains Teen Reproductive Issues
  • Compulsive Shopping, Family, and Fashion in Female Students
  • Mpox Virus Impact in SIVmac239-Infected Macaques
  • Epigenetic Mechanisms Shaping Thyroid Cancer Therapy

Categories

  • Agriculture
  • Anthropology
  • Archaeology
  • Athmospheric
  • Biology
  • Bussines
  • Cancer
  • Chemistry
  • Climate
  • Earth Science
  • Marine
  • Mathematics
  • Medicine
  • Pediatry
  • Policy
  • Psychology & Psychiatry
  • Science Education
  • Social Science
  • Space
  • Technology and Engineering

Subscribe to Blog via Email

Success! An email was just sent to confirm your subscription. Please find the email now and click 'Confirm Follow' to start subscribing.

Join 4,859 other subscribers

© 2025 Scienmag - Science Magazine

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
No Result
View All Result
  • HOME
  • SCIENCE NEWS
  • CONTACT US

© 2025 Scienmag - Science Magazine