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An Indigenous mother in warm weather clothing holds her infant while leaning over a fence

Mother Earth: Climate and Maternal Health Justice

Intern Joy Oloyede explores the links between climate inaction and health inequities for birthing people and babies of color, and the potential uses for AI to reverse these troubling trends.

Read Joy's Blog

Bianca's Story: Turning Pain into Action

Bianca Dickerson Williams, JD
Founder and Executive Director, Fighting Our Injustices for Women of Color

Visit Bianca’s website.

From Story to Data: Understanding Natural Language Processing

Maria Antoniak, PhD
Young Investigator, Allen Institute for Artificial Intelligence

Visit Dr. Antoniak’s website.

From Data to Research: NLP & Maternal Health Use Cases

Angela D. Thomas, DrPH, MPH, MBA
Vice President, Healthcare Delivery Research, MedStar Health

The Giving Voice to Mothers study: inequity and mistreatment during pregnancy and childbirth in the United States*
Vedam S, Stoll K, Khemet Taiwo T, Rubashkin N, Cheyney M, Strauss N, McLemore M, Caden M, Nethery E, Rushton E, Schummers L, Declercq E, GVtM-US Steering Council

Allan Fong, MS
Senior Research Scientist and Data Scientist, MedStar Health

A Machine Learning Approach to Reclassifying Miscellaneous Patient Safety Event Reports
Fong A, Behzad S Pruitt Z, Ratwani RM.

Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward
Fong A.

Integrating natural language processing expertise with patient safety event review committees to improve the analysis of medication events
Fong A, Harriott N, Walters DM, Foley H, Morrissey R, Ratwania RM.

Exploration and Initial Development of Text Classification Models to Identify Health Information Technology Usability-Related Patient Safety Event Reports
Fong A, Komolafe T, Adams KT, Cohen A, Howe JL, Ratwani RM.

Mark Clapp, MD, MPH
Maternal-Fetal Medicine Specialist, Physician Investigator, Massachusetts General Hospital   

Comparison of Natural Language Processing of Clinical Notes with a Validated Risk-Stratification Tool to Predict Severe Maternal Morbidity *
Clapp MA, Kim E, James KE, Perlis RH, Kaimal AJ, McCoy TH, Easter SR.

Natural language processing of admission notes to predict severe maternal morbidity during the delivery encounter.
Clapp MA, Kim E, James KE, Perlis RH, Kaimal AJ, McCoy TH.

Anna Wexler, PhD
Assistant Professor of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine

Pregnancy and health in the age of the Internet: A content analysis of online “birth club” forums*
Wexler A, Davoudi A, Weissenbacher D, Choi R, O’Connor K, Cummings H, Gonzalez-Hernandez G.

Amulya Yadav
Assistant Professor, PNC Technologies Career Development and Associate Director, Center for Socially Responsible Artificial Intelligence, Penn State University

A Continual Pre-training Approach to Tele-Triaging Pregnant Women in Kenya*
Zhang W, Guo H, Ranganathan P, Patel J, Rajasekharan S, Danayak N, Gupta M, Yadav A.

Harnessing Social Media to Identify Homeless Youth At-Risk of Substance Use*
Zi-YiDou, Anamika Barman-Adhikari, Fei Fang, Amulya Yadav.

New AI tool helps provide better care to pregnant women in Kenya*
Ford J.

A Socially Conscious Approach to NLP: Addressing Bias and Racism

Ruha Benjamin, PhD
Professor, Department of African American Studies, Princeton University and Founding Director, Ida B. Wells Just Data Lab

Visit Dr. Benjamin’s website.

Moderator: Karey M. Sutton PhD

From Data to Action: What Public Health, Hospitals and Health Systems Can Do

Justin Schonfeld, PhD
Research Scientist, Public Health Agency of Canada

Challenges and opportunities for public health made possible by advances in natural language processing*
Baclic O, Tunis M, Young K, Doan C, Swerdfeger H, Schonfeld J.

Carlos Siordia, PhD, MS
Lead Interdisciplinary Epidemiologist, Division of Violence Prevention, National Center for Injury Prevention and Control

Artificial Intelligence, Public Trust, and Public Health*
Siordia C, Khoury MJ.

Simon Linwood, MD, MBA
Chief Information Officer and Chief Information Officer, University of California Riverside Health and School of Medicine

Unjust: the health records of youth with personal/family justice involvement in a large pediatric health system*
Boch S, Sezgin E, Ruch D, Kelleher K, Chisolm D, Lin S.

Locating Youth Exposed to Parental Justice Involvement in the Electronic Health Record: Development of a Natural Language Processing Model*
Boch S, Hussain S, Bambach S, DeShetler C, Chisolm D, Linwood S.

Operationalizing and Implementing Pretrained, Large Artificial Intelligence Linguistic Models in the US Health Care System: Outlook of Generative Pretrained Transformer 3 (GPT-3) as a Service Model
Sezgin E, Sirrianni J, Linwood SL.

Ethical artificial intelligence in paediatrics.
Boch S, Sezgin E, Lin Linwood S.


* Denotes open access article. Others are subject to copyright limitations.