BACKGROUND: Efforts toward tuberculosis management and control are challenged by the emergence of Mycobacterium tuberculosis (MTB) resistance to existing anti-TB drugs. This study aimed to explore the potential of machine learning algorithms in predi...
OBJECTIVE: Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these settings, accurate patient prognostication is both difficult and essential for high-quality patient care. With the ultimate goal of ...
Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these low-resource settings, effective triage of patients with TBI-including the decision of whether or not to perform neurosurgery-is critical in op...
Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency v...
Journal of health organization and management
Nov 10, 2025
PURPOSE: The purpose of this study is to investigate the relationship between artificial intelligence (AI) and employee performance in Uganda's healthcare institutions, with a specific focus on exploring the mediating effects of perceived ease of use...
International journal for equity in health
May 30, 2025
BACKGROUND: Uganda, like other United Nations (UN) member states, has undertaken to achieve Universal Health Coverage (UHC) by 2030 in line with Sustainable Development Goal (SDG) 3 targets. However, if this target is to be achieved, efforts will nee...
BACKGROUND: In pursuit of applying universal non-biased Artificial Intelligence (AI) in healthcare, it is essential that data from different geographies are represented.
Journal of the International AIDS Society
Mar 1, 2020
INTRODUCTION: Real-time electronic adherence monitoring (EAM) systems could inform on-going risk assessment for HIV viraemia and be used to personalize viral load testing schedules. We evaluated the potential of real-time EAM (transferred via cellula...
The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
Mar 1, 2018
OBJECTIVE: To evaluate the feasibility of Deep Learning-based detection and classification of pathological patterns in a set of digital photographs of chest X-ray (CXR) images of tuberculosis (TB) patients.
Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumpt...
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