Papers & Publications
How AI and data can change the fight against Malaria in Kenya
Author: Dr. Lisette Schutte, Solution Lead Epidemic Preparedness, PharmAccess, How AI and data can change the fight against Malaria in Kenya, PharmAccess, Nov 4, 2025
Artificial Intelligence to Connect Private Sector Malaria Diagnosis and Case Reporting in Kisumu County, Kenya
Naomy Onyuka, Lisette Schutte, Nathalie Houben, Alloys K’oloo, Felix Bahati, Lilyana Dayo, Tobias F. Rinke de Wit, Artificial Intelligence to Connect Private Sector Malaria Diagnosis and Case Reporting in Kisumu County, Kenya. AI In Health Africa Conference, Nov 5, 2025
Assessing accuracy and performance: of recording mRDT results, result stability over time, and AI RDT reading, a collection of publications from a 4-country study in Africa
Publication collection for a 4-country operational research study in Benin, Nigeria, Uganda, andCote d'Ivoire. View full collection , BMC, Springer Nature November 2025
Highlighted paper: Lindblade, K.A., Mpimbaza, A., Ngufor, C. et al. Assessing the accuracy of the recording and reporting of malaria rapid diagnostic test results in four African countries: methods and key results.Malar J24, 206 (2025). https://doi.org/10.1186/s12936-025-05459-7
Task Specific Computer Vision Versus Large Multi-Modal Models for Diagnostic Test Interpretation – A Benchmarking Study [version 1]
Mendonca R, Smedinghoff S, Li B, Gupta K, Ruan Y, Morris S, Isabelli P, Hattery D, Ratevosian J, Mateen B. Task Specific Computer Vision Versus Large Multi-Modal Models for Diagnostic Test Interpretation – A Benchmarking Study[version 1]. VeriXiv 2025, 2:272
(pre-print)
HealthPulse AI: Enhancing Diagnostic Trust and Accessibility in Under-Resourced Settings through AI [version 1]
Frade S, Rech D, Mendonca R, Cooper S, Morris S, Lee H, Gupta K, Sihan Li B, Ruan Y, Hattery D, Marucheck M, Isabelli P, "HealthPulse AI: Enhancing Diagnostic Trust and Accessibility in Under-Resourced Settings through AI" [version 1]. VeriXiv 2025, 2:54
(preprint)
Malaria RDT (mRDT) interpretation accuracy by frontline health workers compared to AI in Kano State, Nigeria [version 1]
Frade S, Cooper S, Smedinghoff S, Hattery D, Ruan Y, Isabelli P, Ravi N, McLaughlin M, Metz L, Finette B, "Malaria RDT (mRDT) interpretation accuracy by frontline health workers compared to AI in Kano State, Nigeria" [version 1]. VeriXiv 2024, 1:3
(preprint)
Pilot Results: Elephant Health Nigeria, AI-powered malaria case management
Author: Jonathan Dola-Timothy, Elephant Nigeria, July 2024, Elephant Partners with Audere to increase testing rates for malaria, full Case Study here
Use of a health worker-targeted smartphone app to support quality malaria RDT implementation in Busia County, Kenya: A feasibility and acceptability study
Skjefte M, Cooper S, Poyer S, Lourenço C, Smedinghoff S, Keller B, Wambua T, Odour C, Frade S, Waweru W, "Use of a health worker-targeted smartphone app to support quality malaria RDT implementation in Busia County, Kenya: A feasibility and acceptability study", PLoS ONE 19(3): e0295049. https://doi.org/10.1371/journal.pone.0295049
Malaria RDT interpretation accuracy of health workers compared to artificial intelligence (AI) and Panel Read in Kano State, Nigeria
Sasha Frade, Shawna Cooper, Sam Smedinghoff, David Hattery, Yongshao Ruan, Paul Isabelli, Ravi Nirmal, Megan McLaughlin, Lynn Metz, Barry Finette, "Malaria RDT interpretation accuracy of health workers compared to artificial intelligence (AI) and Panel Read in Kano State, Nigeria", 2023 ASTMH Conference, Chicago, IL, USA, 2023 Poster Session 5378.
Transforming Rapid Diagnostic Tests into Trusted Diagnostic Tools in LMIC using AI
Krishnam Gupta, Yongshao Ruan, Ahmed Ibrahim, Rouella Mendonca, Shawna Cooper, Sarah Morris, and David Hattery, "Transforming Rapid Diagnostic Tests into Trusted Diagnostic Tools in LMIC using AI", 2023 IEEE Conference on Artificial Intelligence (CAI), Santa Clara, CA, USA, 2023, pp. 306-308, doi: 10.1109/CAI54212.2023.00136.