Mark Jordans
ID: UNCST-2020-R014861
|
Evaluating the effectiveness of Can’t Wait to Learn in formal education in Uganda
REFNo: SS1024ES
1)To assess the feasibility of the intervention and study (cRCT) methods,
2)To evaluate the effectiveness of CWTL in improving reading and numeracy outcomes of children in Primary 3 (P3),
3)To assess the value for money of CWTL and other factors for EdTech programme scale-up.
|
Netherlands |
2021-10-22 |
2024-10-22 |
Social Science and Humanities |
Non-Clinical Trial |
Non-degree Award |
|
Juliet Nattabi Kigongo
ID:
|
Vanishing Glaciers of the Rwenzori Mountains National Park (Uganda)
REFNo: NS291ES
Vanishing Glaciers project aims for the first
time to explore the streams of mountain
biogeochemistry, and the living
microorganisms of these remote
ecosystems, now strongly impacted by
climate change.
The project’s main goals are:
• To establish the census of microbial
life of the world’s glacier-fed
streams.
• To predict the future changes of the
glacier-fed streams biogeochemistry
as the world’s glaciers recede
1. Study the microbial life from glacier-fed streams
2.Study the biogeochemistry of glacier-fed streams
3.Study the environment of glacier-fed streams, including glaciological parameters
|
Uganda |
2021-10-22 |
2024-10-22 |
Natural Sciences |
Non-Clinical Trial |
Non-degree Award |
|
Andrew Katumba
ID:
|
Performance of a novel, rapid AI-driven screening tool for improved COVID-19 patient care and management in Uganda
REFNo: SIR74ES
General Objective
To develop and deploy AI-driven screening tools for improved care and management of COVID-19 patients. This will be achieved through the following specific objectives:
Specific Objectives
1. To collect, curate and label Lung Ultrasound (LUS) images from COVID-19 patients and patients with related pulmonary pathologies such as non-COVID-19 derived pneumonia, yielding a generalizable and representative image/video dataset.
2. To develop robust image-driven machine learning (ML) models for detection and screening of COVID-19 using the data from objective 1.
3. To build mobile and web-based applications that integrate the ML models, for online (real-time) and offline COVID-19 screening.
4. To pilot the developed applications and evaluate their clinical efficacy in COVID-19 screening.
|
Uganda |
2021-10-22 |
2024-10-22 |
Engineering and Technology |
Non-Clinical Trial |
Non-degree Award |
.jpg)
|
Moffat Nyirenda Joha
ID: UNCST-2020-R019333
|
Identification and characterization of Diabetes in low-resource Populations
REFNo: HS1791ES
The secondary study objectives are:
1. To establish a base-line cohort of well-characterised people with diabetes to understand disease progression of the different phenotypes, including uptake and response to treatment.
2. To identify and recruit a cohort of non-diabetic volunteers (including prediabetes i.e., at high risk of developing diabetes) for longitudinal follow-up.
i. To identify a cohort of non-diabetic people in order to measure the incidence of disease in the future estimate incidence of diabetes.
ii. To assess the burden and rates of progression of vascular complications associated with the different phenotypes of dysglycaemia.
|
Malawi |
2021-10-22 |
2024-10-22 |
Medical and Health Sciences |
Non-Clinical Trial |
Non-degree Award |
|
Frederick Mubiru Edward
ID:
|
Market Research on User Perspectives for a 4-month Depot Medroxyprogesterone Acetate Subcutaneous (DMPA-SC) Product
REFNo: HS1792ES
1. To solicit input from potential and current contraceptive injectable users, as well as males/partners, on acceptability and implications for having multiple injectable products of different durations in the market, with an emphasis on a 4-month DMPA-SC product as well as a potential 6-month injectable
2. To co-create marketing strategies/messages with current and potential users for the introduction and differentiation of new injectable products
|
Uganda |
2021-10-22 |
2024-10-22 |
Medical and Health Sciences |
Non-Clinical Trial |
Non-degree Award |
|
| View |
|
Sort By: |
|
|
|
| |
|