Maternal, reproductive, and sexual health are critical issues in Africa that have far-reaching implications for the continent’s development. Despite significant progress made in recent years, Africa still faces many challenges in these areas, including high rates of maternal mortality, poor access to family planning, and the spread of sexually transmitted infections (STIs). Over the years, innovative solutions, including artificial intelligence applications, have demonstrated encouraging potential for enhancing the delivery of maternal, sexual, and reproductive health and rights information and services, but the potential risks and harm that come from using AI in this sector cannot be overlooked.
Under the innovation pillar of the AI4D Africa program, we set out to support 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. With Responsible AI considerations, we can ensure that AI is developed and implemented in a way that is ethical, transparent, and accountable, to ensure that it benefits all members of society. Last year, we announced that this hub will be set up and managed by Infectious Disease Institute at Makerere University, Makerere University AI Lab and Sunbird AI
After reviewing over 80 submissions from different countries across the continent, here are the ten teams selected to join the hub and for on exciting solutions to the challenges facing maternal, reproductive and sexual health in Africa:
Project 1:
Harnessing the power of Artificial Intelligence to augment patients’ knowledge, understanding and behaviours with Sexually Transmitted Infections.
Organization:
mDoc Healthcare
Country:
Nigeria
Project summary:
This project aims to develop an AI enabled Chatbot that will provide personalised guidance to pregnant women and their partners on STIs.
Project 2
Sexually transmitted disease monitoring and assistance tool design in Ethiopian higher education institute
Organization:
Addis Ababa Science and Technology University
Country:
Ethiopia
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.
Project 3
Prediction of miscarriages among women seeking antenatal care in Uganda: A machine learning approach
Organization:
Makerere University
Country:
Uganda
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.
Project 4
Machine Learning for identifying teenage patients at risk of gestational hypertension
Organization:
Pan African Information Communication Technology
Country:
Namibia
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. This project will; gather clinical datasets relating to teenage pregnancies from the Namibian context, train the dataset based on nine binary classification models and test and compare the prediction performance of the different models trained.
Project 5
Organization:
Makerere University
Country:
Uganda
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.
Project 6
Using Machine Learning and Artificial Intelligence (AI) modelling to identify high-risk sub-population eligible for PrEP and willing to pay for the services.
Organization:
The Medical Concierge Group
Country
Uganda
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.
Project 7
Artificial Intelligence for screening of TB among people living with HIV
Organization:
Muhimbili University of Health and Allied Sciences
Country:
Tanzania
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
Project 8
Utilizing AI to Promote Sexual and Reproductive Health Outcomes for Adolescents with Disabilities in Ghana
Organisation
University of Ghana, Legon
Country:
Ghana
Project summary:
This project seeks to utilize 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.
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
Organization:
University of Embu
Country:
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
Project 10
Leveraging Artificial Intelligence Techniques To Inform Choice Of Modern Contraceptives Among Adolescent Girls And Young Women.
Organisation:
Mbarara University of Science and Technology
Country:
Uganda
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 occurrence contraceptive side effects and contraceptive failure.
We are looking forward to the work that these teams will do and how the solutions they develop will impact the maternal, reproductive and sexual health sector in Africa. In addition to these sub grantees, the hub has established the HASH network. The HASH Network welcomes enthusiasts, researchers and organisations working in the AI and/or the maternal, reproductive and sexual health (MSRH) space. The overall goal of the Network is to create a collaborative platform for developing resilient and sustainable systems for MSRH through responsible AI. The HASH sub grantees and consortium are the founding members of the HASH Network.
Are you interested in joining this network, simply fill in this form