ABSTRACT
In lower-income countries, indicators for sexual, reproductive, and maternal health are lagging relative to other health indicators. For example, the levels of maternal mortality and access to contraception are generally off pace to meet Sustainable Development Goals to reduce maternal mortality to less than 70 per 100,000 live births and ensure universal access to sexual and reproductive health-care services. While the ongoing COVID-19 pandemic takes center stage, there is an urgent need to scale further innovation and solutions for improving maternal, sexual, and reproductive health and rights while strengthening health systems for integrated and sustainable health services.
Digital technologies, including artificial intelligence (AI) applications, have demonstrated encouraging potential for enhancing the delivery of maternal, sexual, and reproductive health and rights information and services. However, significant concerns remain about the potential harms and risks of using digital technology in this sector. The main objective of this project is to establish a research hub whose aim is to advance maternal, sexual, and reproductive health and rights while strengthening health systems in sub-Saharan Africa through the responsible development and deployment of AI innovations. Responsible AI innovations are defined as those that are ethical, inclusive, and equitable, respect human rights, and contribute to environmental sustainability.
The hub on AI for sexual, reproductive, and maternal health in Africa is complimentary to four similar hubs on gender and inclusion, climate change, agriculture, and education that are being developed by IDRC’s AI for Development Africa initiative. It will identify, validate, and document priority themes, strengthen the capacity of African innovators, researchers, and policymakers, and increase and strengthen the number of homegrown AI innovations in maternal, sexual, and reproductive health and rights while strengthening health systems in Africa.
LOCATION
Uganda, The Infectious Disease Institute Limited
TOTAL FUNDING
CA$ 1,198,700
PRINCIPAL INVESTIGATOR:
- Rosalind Parkes-Ratanshi
SUBPROJECTS
| Project 1 — Harnessing the power of Artificial Intelligence to augment patients’ knowledge, understanding and behaviours with Sexually Transmitted Infections | Project Summary: This project aims to develop an AI enabled Chatbot that will provide personalised guidance to pregnant women and their partners on STIs. | |
| Organization: mDoc Healthcare | Country: Nigeria | |
| Project 2 — Sexually transmitted disease monitoring and assistance tool design in Ethiopian higher education institute | Project Summary: This project aims to use mathematical modelling to identify key variables that predict sexually transmitted diseases among university students. The team will also develop a chatbot to disseminate information and help students get help freely. | |
| Organization: Addis Ababa Science and Technology University | Country: Ethiopia | |
| Project 3 — Prediction of miscarriages among women seeking antenatal care in Uganda: A machine learning approach | Project Summary: This project will build a web application that will use a classification machine learning algorithm to predict the risk of miscarriage among women seeking antenatal care, while identifying the major factors that influence a pregnancy ending in a miscarriage. | |
| Organization: Makerere University | Country: Uganda | |
| Project 4 — Machine Learning for identifying teenage patients at risk of gestational hypertension | Project Summary: This project will develop an ML model by comparing the prediction performance of nine classification models to identify teenage patients at risk of gestational hypertension. | |
| Organization: Pan African Information Communication Technology | Country: Namibia | |
| Project 5 | Project Summary: This project will develop a smart, robust, and rapid screening solution for high-risk pregnancies utilising a combination of US imaging modalities, and a computational platform backed by AI in the form of Deep Learning Models. | |
| Organization: Makerere University | Country: Uganda | |
| Project 6 — Using Machine Learning and Artificial Intelligence (AI) modeling to identify high-risk sub-population eligible for PrEP and willing to pay for the services. | Project Summary: Using existing datasets, this project will leverage ML and AI modelling to identify, quantify, analyse, and map high-risk populations that are eligible for PrEP and can pay for the services. | |
| Organization: The Medical Concierge Group | Country: Uganda | |
| Project 7 — Artificial Intelligence for screening of TB among people living with HIV | Project Summary: This team will use a previously developed tool for screening TB using chest X-Rays to identify the disease in people living with HIV. | |
| Organization: Muhimbili University of Health and Allied Sciences | Country: Tanzania | |
| Project 8 — Utilising AI to Promote Sexual and Reproductive Health Outcomes for Adolescents with Disabilities in Ghana | Project Summary: This project seeks to utilise machine learning to break the barriers inhibiting adolescents with hearing, speech and visual disabilities from accessing SRH information and services. A mixed-methods research design will be adopted to collect data from in-school adolescents with hearing, speech and visual disabilities, as well as key stakeholders. | |
| Organization: University of Ghana, Legon | Country: Ghana | |
| Project 9 — BESHTE: A Chatbot to enhance HIV testing, status awareness, and status disclosure among adolescent boys and girls and young men and women in Kenya | Project Summary: This project will build a Chatbot that will be used to increase HIV knowledge and HIV testing, while enhancing status awareness and status disclosure to sexual partners within the population group. It will also address discrimination and HIV-related stigma toward adolescents and young adults seeking testing and treatment. | |
| Organization: University of Embu | Country: Kenya | |
| Project 10 — Leveraging Artificial Intelligence Techniques To Inform Choice Of Modern Contraceptives Among Adolescent Girls And Young Women. | Project Summary: This research project will follow up young girls and adolescent women aged 15-24 years using selected modern contraceptive methods and attending family planning clinics for a period of 12 months. The data collected will be used to develop an AI model that will predict likelihood of contraceptive side effects and contraceptive failure. | |
| Organization: Mbarara University of Science and Technology | Country: Uganda | |