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Artificial intelligence for tuberculosis control: a scoping review of applications in public health
Menon, S.; and K. Ghislein Kuro
(2025)
J Glob Health. 2025;15:04192. This scoping review highlights the potential of AI-driven predictions in national TB programmes to enhance diagnostics, track trends, and strengthen public health surveillance. While promising for reducing transmission and support-
ing TB care in low-resource settings,
...
these models require large-scale validation to ensure real-world applicability, especially for high-risk groups
more
This guidance addresses one type of generative AI, large multi-modal models (LMMs), which can accept one or more type of data input and generate diverse outputs that are not limited to the type of data fed into the algorithm. It has been predicted that LMMs will have wide use and application in heal
...
th care, scientific research, public health and drug development. LMMs are also known as “general-purpose foundation models”, although it is not yet proven whether LMMs can accomplish a wide range of tasks and purposes.
more
TArtificial intelligence (AI) is transforming health systems, reshaping how care is planned, delivered and governed. This report presents the first assessment of AI integration into health systems across the whole of the WHO European Region, based on findings from the 2024–2025 survey on AI for he
...
alth care. It examines national strategies, governance models, legal and ethical frameworks, workforce readiness, data governance, stakeholder engagement, private sector roles and the uptake of AI applications. Drawing on insights from 50 Member States, the report explores how countries are navigating opportunities and challenges, highlighting emerging trends, gaps and practices to guide policy-makers towards coherent, ethical and people-centred approaches to AI in health care.
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A reference guide for decision-makers that outlines key issues, checklists, and templates to consider when providing or receiving international aid.
Key resources include the Manual for Disaster Response Teams, which helps experts plan public communication, exchange information, and manage media, ensuring crucial data reaches humanitarian actors
Between April 2018 and November 2020, the Democratic Republic of Congo (DRC) experienced its 11th Ebola virus disease (EVD) outbreak. Tanzania’s cross-border interactions with DRC through regular visitors, traders, and refugees are of concern, given the potential for further spread to neighboring
...
countries. This study aimed to estimate the risk of introducing EVD to Tanzania from DRC. National data for flights, boats, and car transport schedules from DRC to Tanzania covering the period of May 2018 to June 2019 were analyzed to describe population movement via land, port, and air travel and coupled with available surveillance data to model the risk of EVD entry. The land border crossing was considered the most frequently used means of travel and the most likely pathway of introducing EVD from DRC to Tanzania. High probabilities of introducing EVD from DRC to Tanzania through the assessed pathways were associated with the viability of the pathogen and low detection capacity at the ports of entry. This study provides important information regarding the elements contributing to the risk associated with the introduction of EBV in Tanzania. It also indicates that infected humans arriving via land are the most likely pathway of EBV entry, and therefore, mitigation strategies including land border surveillance should be strengthened.
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