The objective of this project is to develop a technology-based solution to assist the Department of Health (DoH) to identify, track and monitor Drug-Resistant Tuberculosis (DR-TB) patients in the Nelson Mandela Bay area.
LeguPro is a protein-rich pasta, which is produced from non-traditional pasta ingredients such as peanuts, soybeans, and chickpeas. It is a cost-effective nutrient-dense high protein, healthy instant noodle product and aims to give consumers an alternative staple food product to be consumed as is or...
Universal access, low student engagement, informal curriculum
alignment and limited measurability of educational outcomes are
all key problems with the current remote or virtual learning
programs undertaken in large scale public-private educational
technology deployments. COVID-19 has further widened the gap
between remote, peri-urban, low-income public sector students
and private education students.
IDEA has created an outcome, data-driven and interactive virtual
school solution that is device and connectivity agnostic. Working
on a mobile phone, tablet, computer or projector the
iResponse is an AI-driven digital health platform designed to implement preventive health diagnostics, improve patient care, send out early warning and alert notification, track, predict, analyse and deal with COVID-19 infectious disease threat in Nigeria.
It helps better the human condition and bring about a better future to Nigerians using Artificial Intelligence (AI), big data analytics and digital technologies to manage and quarantine the exposed person, and deal with the pandemic in Nigeria.
COVID-19 disease cause pulmonary infections, which could be observed by CT images of the lungs as well as chest X-ray images. Clinicians have been able to observe and diagnose similar infection such pneumonia using this approach. In fact asymptomatic breast cancer and diabetes testing can currently be done using AI image processing.
A anonymised dataset of chest x ray images of Covid-19 infected patients as well as healthy patients is sampled. A convolutional neural network model is trained to analyse chest x -ray images, detect and label COVID-19 infected cases. Mobile chest X ray
TjopTjop is a mobile app developed by the, NWU Faculty of Engineering Medical Device Development and Commercialisation group, to assist schools, businesses, and other institutions to easily collect and store health screening information from students, pupils, staff and clients. It saves time and effort at the screening stations, makes stored data available to the relevant people who needs to view the summarized data and act proactively when the results are out of range. For children we create QR codes as ID cards, and we use barcode IDs (both books and card versions) to identify the adults we
My innovation gathers real time data of interactions and contact between people as they go about their daily lives. This information is stored in a secure server used by the medical department to protect identity.
When a person who has this app running on their smart phone is tested positive for COVID-19, medical personell can then retrieve their app ID and access the data which will tell them who the person was recently in contact with for the past 31 days.
Through the app a health personel can contact the potentially infected people and find out if they are experiencing any symptoms
Baobab LIMS is an African-led innovation that was developed as part of the B3Africa consortium. It is an affordable sample and laboratory management tool for biobanking that has been implemented in low- and middle-income countries (LMICs), who previously (due in part to financial constraints), were...