AIMC Topic: Tanzania

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Integrating digital technologies in clinical dentistry training: a framework for competency-based education.

BMC medical education
BACKGROUND: Integrating digital technologies in clinical dentistry training is increasingly recognized as essential for modernizing competency-based education. However, structured frameworks for digital technology adoption in dental training are lack...

Predicting risk of early-onset sepsis in low-resource neonatal units using routine healthcare data: development and evaluation of multivariable statistical and machine learning models.

BMJ paediatrics open
BACKGROUND: Neonatal sepsis is a major cause of morbidity and mortality in low-resource settings and accurate, context-appropriate diagnostic methods are urgently needed to improve clinical outcomes.

A data-intensive framework for evaluating ecological and human health impacts of soil potentially toxic elements (PTEs) in the mining-endemic region of Singida, Tanzania.

Environmental geochemistry and health
Uncontrolled soil contamination by potentially toxic elements (PTEs) poses serious threats to environmental and public health in mining-intensive regions. Against this background, this study assessed the distribution, sources, ecological impact, and ...

Mucosal immune responses and intestinal microbiome associations in wild spotted hyenas (Crocuta crocuta).

Communications biology
Little is known about host-gut microbiome interactions within natural populations at the intestinal mucosa, the primary interface. We investigate associations between the intestinal microbiome and mucosal immune measures while controlling for host, s...

Banana Leaves Imagery Dataset.

Scientific data
In this work, we present a dataset of banana leaf imagery, both with and without diseases. The dataset consists of 11,767 images, categorized as follows: 3,339 healthy images, 3,496 images of leaves affected by Black Sigatoka and 4,932 images of leav...

Deciphering the climate-malaria nexus: A machine learning approach in rural southeastern Tanzania.

Public health
OBJECTIVES: Malaria remains a critical public health challenge, especially in regions like southeastern Tanzania. Understanding the intricate relationship between environmental factors and malaria incidence is essential for effective control and elim...

Prevention of adverse HIV treatment outcomes: machine learning to enable proactive support of people at risk of HIV care disengagement in Tanzania.

BMJ open
OBJECTIVES: This study aimed to develop a machine learning (ML) model to predict disengagement from HIV care, high viral load or death among people living with HIV (PLHIV) with the goal of enabling proactive support interventions in Tanzania. The alg...

Reagent-free detection of Plasmodium falciparum malaria infections in field-collected mosquitoes using mid-infrared spectroscopy and machine learning.

Scientific reports
Field-derived metrics are critical for effective control of malaria, particularly in sub-Saharan Africa where the disease kills over half a million people yearly. One key metric is entomological inoculation rate, a direct measure of transmission inte...

Machine learning for predicting cognitive deficits using auditory and demographic factors.

PloS one
IMPORTANCE: Predicting neurocognitive deficits using complex auditory assessments could change how cognitive dysfunction is identified, and monitored over time. Detecting cognitive impairment in people living with HIV (PLWH) is important for early in...