<p>Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights </p>

Henrique A. Lima; Zorays Moazzam; Pedro  Trocolli; Leonardo Rocha; Adriana  Pagano; Felipe F.  Martins; Lucas T.  Brabo; Zilma  Reis; Lisa Keder; Aliya Begum; Marcelo H. Mamede; Timothy M.  Pawlik; Vivian  Resende

doi:10.21955/gatesopenres.1117192.1

Home Browse Context-sensitive Evaluations of Large Language Models for Maternal...

Document

NOT PEER REVIEWED

Download

metrics

VIEWS

downloads

SEE MORE DETAILS

CITE

How to cite this document:

Lima HA, Moazzam Z, Trocolli P et al. Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights [version 1; not peer reviewed]. Gates Open Res 2025, 9:21 (document) (https://doi.org/10.21955/gatesopenres.1117192.1)

NOTE: it is important to ensure the information in square brackets after the title is included in this citation.

Discussion

Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights

Henrique A. Lima¹, Zorays Moazzam², Pedro Trocolli³, Leonardo Rocha⁴, Adriana Pagano⁵, Felipe F. Martins⁶, Lucas T. Brabo⁶, Zilma Reis¹, Lisa Keder ⁷, Aliya Begum⁸, Marcelo H. Mamede¹, Timothy M. Pawlik⁹, Vivian Resende¹

Published 08 May 2025 (https://doi.org/10.21955/gatesopenres.1117192.1)

Author Affiliations

¹ Federal University of Minas Gerais School of Medicine, Belo Horizonte, Brazil
² Henry Ford Hospital, Detroit, Michigan, USA
³ Federal University of Minas Gerais School of Medicine, Belo Horizente, Brazil
⁴ Computer Science Department, Federal University of São João Del-Rei, São João Del-Rei, Brazil
⁵ Federal University of Minas Gerais School of Languages, Belo Horizonte, Brazil
⁶ Asenion, Belo Horizonte, Brazil
⁷ Department of Gynaecology and Obstetrics, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
⁸ Department of Gynaecology and Obstetrics, The Aga Khan University, Karachi, Sindh, Pakistan
⁹ Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA

Copyright © 2025 Lima HA et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Metrics
28 Views
6 Downloads

DOWNLOAD 226.17 KB

CITE

Published 08 May 2025

Discussion

Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights
[version 1; not peer reviewed]

Author Affiliations

Abstract

Gates Foundation grant number

INV-070496

Competing Interests

No competing interests were disclosed

Keywords

LLM Evaluations, LLM Biases

Comments

0 Comments

All commenters must hold a formal affiliation as per our Policies. The information that you give us will be displayed next to your comment.

User comments must be in English, comprehensible and relevant to the article under discussion. We reserve the right to remove any comments that we consider to be inappropriate, offensive or otherwise in breach of the User Comment Terms and Conditions. Commenters must not use a comment for personal attacks. When criticisms of the article are based on unpublished data, the data should be made available.

I accept the User Comment Terms and Conditions

Affiliation

Please enter your institution.

Note: To add your institution or organisation, start typing the name and then select the correct name from the list. Where applicable, the name will appear in both the original language and in English. Do not paste in the name. If the name does not appear in the drop-down list, we will display the information you have entered.

Please select your country/region.

Competing Interests

Please disclose any competing interests that might be construed to influence your judgment of the content's validity or importance.

Last Updated: 2 October 2017

Gates Open Research is an open access publishing platform controlled by the Gates Foundation (“Foundation”). This website, https://GatesOpenResearch.org (“Website”), is hosted and operated by F1000 Research Limited (“Service Provider”) on behalf of the Foundation.

BY CHECKING THE BOX NEXT TO “I ACCEPT THE USER COMMENT TERMS AND CONDITIONS” BEFORE YOU SUBMIT YOUR FIRST USER COMMENT, YOU AGREE TO BE BOUND BY THE GENERAL TERMS AND CONDITIONS AND THESE ADDITIONAL TERMS AND CONDITIONS EVERY TIME YOU SUBMIT A USER COMMENT. PLEASE DO NOT SUBMIT A USER COMMENT ON THIS WEBSITE IF YOU DO NOT AGREE TO THESE TERMS AND CONDITIONS. TERMS NOT DEFINED IN THESE ADDITIONAL TERMS AND CONDITIONS SHALL HAVE THE MEANING PROVIDED IN THE GENERAL TERMS AND CONDITIONS.

As provided in the General Terms and Conditions, neither the Foundation nor the Service Provider screen, edit, publish or review Comments prior to their appearance on the website and Comments do not reflect the views or opinions of the Foundation or the Service Provider, its agents or affiliates. Comments reflect the view and opinion of the person who posts such view or opinion. To the extent permitted by applicable laws the Foundation and the Service Provider shall not be responsible or liable for the Comments or for any loss, cost, liability, damages or expenses caused and or suffered as a result of any use of and/or posting of and/or appearance of the Comments on this website.
The Foundation reserves the right, but is under no obligation, to (a) monitor User Comments, and (b) remove any User Comments which it considers in its absolute discretion to be inappropriate, offensive or otherwise in breach of these User Comment Terms and Conditions.
By posting User Comments on the Website, you thereby warrant and represent that:
1. You are entitled to post any User Comments posted by you on this Website and have all necessary licenses and consents to do so;
2. the User Comments posted by you on this Website do not infringe any intellectual property right, including without limitation copyright, patent or trademark, or other proprietary right of any third party;
3. the User Comments posted by you on this Website do not contain any obscene, defamatory, libellous, offensive, indecent or otherwise unlawful material;
4. the User Comments posted by you on this Website do not violate any right of privacy or other rights of any person or entity;
5. the User Comments posted by you on this Website do not violate any duty of confidentiality which you may owe to anyone else or violate any contract;
6. the User Comments posted by you on this Website do not contain any contaminating or destructive features or devices such as viruses, time bombs or coding designed to interrupt, destroy or limit the functionality of this Website or any of this Website's user's computer equipment or software; and
7. the User Comments posted by you on this Website will not be used to solicit or promote business or custom or present commercial activities or unlawful activity.
By posting User Comments on the Website, you thereby grant to the Foundation and the Service Provider, to the extent acting on the Foundation’s behalf, a non-exclusive royalty-free license to use, reproduce, edit and authorize others to use, reproduce and edit any of User Comments posted by you on this Website in any and all forms, formats or media.
By posting User Comments on the Website, you thereby agree to indemnify and keep indemnified the Foundation and the Service Provider, and their respective affiliates, employees, agents, suppliers, and contractors from and against any and all losses (including without limitation direct, indirect and consequential loss), costs, claims, damages or expenses of whatever nature and howsoever caused arising directly or indirectly from any breach of these additional Terms and Conditions or arising from User Comments posted by you on this Website, including without limitation as a result of any infringement of any intellectual property or other proprietary rights, libel, defamation, obscenity or such User Comments being otherwise unlawful.

Competing Interests

Please disclose any competing interests that might be construed to influence your judgment of the content's validity or importance.

Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights

Discussion

Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights
[version 1; not peer reviewed]

Are you a Gates-funded researcher?

Thank you!

Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights

Discussion Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights [version 1; not peer reviewed]

Are you a Gates-funded researcher?

Thank you!

Discussion

Context-sensitive Evaluations of Large Language Models for Maternal Healthcare in LMICs: Key Insights
[version 1; not peer reviewed]