- In the original trial, midwives successfully completed training to use safe+natal at high rates: 80% passed proficiency tests on the first try, 98% after the second try.
- Detection of key pregnancy complications, particularly hypertensive disorders, increased.
- Successful referral rates to medical facilities for life-threatening conditions significantly increased.
“It was beautiful to hear my baby’s heartbeat.”
Expectant Guatemalan mother
Media
Emory News Center. The challenge of using AI in global health. January 16, 2025.
Think Global Health. Modernizing Traditional Maternal Care in Guatemala: Aiding traditional comadronas to provide quality care to indigenous mothers. March 12, 2024.
Wilson Center New Security Beat. AI in Community Care: Can Co-design Shift the Balance in Maternal Mortality? January 17, 2024
Emory News Center. Emory’s safe+natal program receives Google.org support to use AI for maternal-child health in Guatemala Sept. 12, 2023
Emory Medicine Magazine. How a (married) couple of Emory professors invented a device to monitor fetal health with a smartphone app: Every Mother, Every Baby. Mary Loftus. Winter 2022.
National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Development. “Spotlight: Developing Mobile Health Solutions for Women in Guatemala.” Sept. 14, 2021.
National Institutes of Health, Fogarty International Center – Global Health Matters Newsletter Vol. 20 (No. 4). “mHealth app reduces LMIC pregnancy, delivery risks.” July/Aug 2021.
El Periodico [Guatemalan national newspaper]. “Wuku’ Kawoq, tecnología para evitar muertes maternas” [Wuku’ Kawoq, technology to prevent maternal deaths]. January 12, 2020.
El Periodico [Guatemalan national newspaper]. “Se reduce brecha de mortalidad materna en Chimaltenango, Referencias para asistencia hospitalaria aumentan gracias al uso de tecnología” [Maternal mortality gap in Chimaltenango reduced, Referrals for hospital assistance increase thanks to the use of technology]. May 20, 2019.
Prensa Libre [Guatemalan national newspaper]. “App Salva Vidas: La technología llega en auxilia de las comadronas” [App Saves Lives: The technology arrives to assist midwives]. Aug 26, 2018. pgs. 1, 14-17. Accompanied by online video, “Una app para control materno en Tecpán, Chimaltenango” [An app for maternal control in Tecpán, Chimaltenango].
MSNBC Global Citizen. “App Saves Lives of Maya Women in Guatemala.” Sept 5. 2017
Scientific Papers
2025 Rafiei A, Motie-Shirazi M, Sameni R, Clifford GD, Katebi N. Next-Generation Fetal Heart Monitoring: Leveraging Neural Sequential Modeling for Ultrasound Analysis. IEEE Transactions on Biomedical Engineering July 2. DOI: 10.1109/TBME.2025.3585461
Katebi N, Ahmad M, Motie-Shirazi M, Phan D, Kolesnikova E, Nikookar S, Rafiei A, Korikana MK, Hall-Clifford R, Castro E, Sut R, Coyote E, Venzor Strader A, Ramos E, Rohloff P, Sameni R, Clifford GD. Edge AI for real-time fetal assessment in rural Guatemala. ML4H Conference; Dec 2024.
2024 Katebi N, Bremer W, Nguyen T, Phan D, Jeff J, Armstrong K, Phabian-Millbrook P, Platner M, Carroll K, Shoai B, Rohloff P, Boulet SL, Franklin CG, Clifford GD. Automated Image Transcription for Perinatal Blood Pressure Monitoring Using Mobile Health Technology. PLOS Digital Health October 2; 3 (10): p. e0000588. DOI: doi.org/10.1371/journal.pdig.0000588
2024 Ramos E, Palax IP, Cuxil ES, Iquic ES, Ajqui AC, Miller AC, Chandrasekaran S, Hall-Clifford R, Sameni R, Katebi N, Clifford GD, Rohloff P. Mobil Monitoring Doppler Ultrasound (MoMDUS) study: protocol for a prospective, observational study investigating the use of artificial intelligence and low-cost Doppler ultrasound for the automated quantification of hypertension, pre-eclampsia and fetal growth restriction in rural Guatemala. BMJ Open September 10; 14 (9): p. e090503. DOI: 10.1136/bmjopen-2024-090503.
2023 Katebi N, Sameni R, Rohloff P, Clifford GD. Hierarchical Attentive Network for Gestational Age Estimation in Low-Resource Settings. IEEE Journal of Biomedical and Health Informatics 2023 February 20. DOI: 10.1109/JBHI.2023.3246931.
2023 Nasim Katebi, Whitney Bremer, Tony Nguyen, Daniel Phan, Jamila Jeff, Kirkland Armstrong, Paula Phabian-Millbrook, Marissa Platner, Kimberly Carroll, Banafsheh Shoai, Peter Rohloff, Sheree L. Boulet, Cheryl G. Franklin, Gari D. Clifford. Automated Image Transcription for Perinatal Blood Pressure Monitoring Using Mobile Health Technology, medRxiv 2023.06.16.23291435
2022 N Katebi, GD Clifford Deep Sequence Learning for Assessing Hypertension in Pregnancy from Doppler Signals, medRxiv, 2022.01. 26.22269921
2021 Kulkarni SS, Katebi N, Valderrama CE, Rohloff P, Clifford GD. CNN-based LCD transcription of blood pressure from a mobile phone camera. Frontiers in Artificial Intelligence 2021; 4: p. 543176.
2020.
Katebi N, Marzbanrad F, Stroux L, Valderrama CE, Clifford GD. Unsupervised hidden semi-Markov model for automatic beat onset detection in 1D Doppler ultrasound. Physiological measurement 2020; 41: p. 085007.
2020 Valderrama CE, Ketabi N, Marzbanrad F, Rohloff P, Clifford GD. A review of fetal cardiac monitoring, with a focus on low-and middle-income countries. Physiological measurement 2020; 41: p. 11TR01.
2020 N Katebi, R Sameni, and GD Clifford. Deep Sequence Learning for Accurate Gestational Age Estimation from a $25 Doppler Device. ML4H 2020, NeurIPS.
2020 CEV Cuadros, F Marzbanrad, M Juarez, R Hall-Clifford, P Rohloff, and GD Clifford. Estimating birth weight from observed postnatal weights in a Guatemalan highland community. Physiological Measurement. https://doi.org/10.1088/1361-6579/ab7350
2020 M Juarez, Y Juarez, E Coyote, T Nguyen, C Shaw, R Hall-Clifford, G Clifford, and P Rohloff. Working with lay midwives to improve the detection of neonatal complications in rural Guatemala. BMJ Open Quality, 9(1). http://dx.doi.org/10.1136/bmjoq-2019-000775
2019 C Valderrama Cuadros, L Stroux, N Katebi, E Paljug, R Hall-Clifford, P Rohloff, F Marzbanrad, G Clifford. “An open source autocorrelation-based method for fetal heart rate estimation from one-dimensional Doppler ultrasound.” Physiological Measurement, 40(2):025005. https://doi.org/10.1088/1361-6579/ab033d
2018 B Martinez, E Coyote, R Hall-Clifford, M Juarez, AC Miller, A Francis CE Valderrama, L Stroux, GD Clifford, P Rohloff. mHealth intervention to improve the continuum of maternal and perinatal care in rural Guatemala: a pragmatic, randomized controlled feasibility trial. Reproductive Health, 15(1): 120, 12 pages. https://doi.org/10.1186/s12978-018-0554-z.
2018 CE Valderrama, F Marzbanrad, L Stroux, B Martinez, R Hall-Clifford, C Liu, N Katebi, P Rohloff, and GD Clifford. Improving the Quality of Point of Care Diagnostics with Real-Time Machine Learning in Low Literacy LMIC Settings: Full Paper. Proceedings of ACM SIGCAS Computing and Sustainable Societies (ACMSIGCAS-COMPASS2018). Article 4, 11 pages. https://doi.org/10.475/123_4.
2017 Martinez B, Hall-Clifford R, Coyote E, Stroux L, Valderrama CE, Aaron C, Francis A, Hendren C, Rohloff P, Clifford GD. Agile development of a smartphone app for perinatal monitoring in a resource-constrained setting. Journal of Health Informatics in Developing Countries, 11(1), 19 pages. http://www.jhidc.org/index.php/jhidc/article/view/158/212.
2016 L Stroux, B Martinez, E Coyote Ixen, N King, R Hall-Clifford, P Rohloff & GD Clifford. An mHealth monitoring system for traditional birth attendant-led antenatal risk assessment in rural Guatemala. Journal of Medical Engineering & Technology 40(7-8), 356–371. https://doi.org/10.1080/03091902.2016.1223196.
2014 L Stroux, NE King, S Fathima, R Hall-Clifford, P Rohloff, and GD Clifford. A low-cost perinatal monitoring system for use in rural Guatemala. Appropriate Healthcare Technologies for Low Resource Settings – AHT2014. IET Proceedings: The 8th International Conference – Promoting access to healthcare through technology, 4 pages. DOI: 10.1049/cp.2014.0777.
Conferences and Public Presentations
Katebi N, Ahmad M, Motie-Shirazi M, Phan D, Kolesnikova E, Nikookar S, Rafiei A, Korikana MK, Hall-Clifford R, Castro E, Sut R, Coyote E, Venzor Strader A, Ramos E, Rohloff P, Sameni R, Clifford GD. Edge AI for real-time fetal assessment in rural Guatemala. ML4H Conference; Dec 2024, spotlight presentation, demo track.
Rafiei A, Motie-Shirazi M, Sameni R, Clifford GD, Katebi N. AutoFHR: An interpretable neural temporal model for fetal cardiac activity analysis, ML4H Conference; Dec 2024.
Rafiei A, Clifford GD, Katebi N, Auto-FEDUS: Autoregressive Generative Modeling of Doppler Ultrasound Signals from Fetal Electrocardiograms, AAAI, March 2025.
Nikookar S, Robichaux C, Sameni R, Chandrasekaran S, Clifford GD, Franklin C, Boulet S, Katebi N. A deep embedding approach for clustering BP trajectories to identify hypertensive disorders of pregnancy. Abstract accepted at Georgia CTSA Conference; 2025 for oral presentation.
safe+natal 