Scaling up artificial intelligence to curb infectious diseases in Africa

Otaigbe, Idemudia

doi:10.3389/fdgth.2022.1030427

Cited by 9 publications

(4 citation statements)

References 37 publications

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“…The work in [23] discusses machine ethics and African identities, offering perspectives on MI in Africa. In [24] the authors advocates scaling up MI to curb infectious diseases in Africa. The work in [25] addresses emerging challenges of artificial intelligence in Africa, presented in the context of responsible MI.…”

Section: Literature Reviewmentioning

confidence: 99%

Machine Intelligence in Africa: a survey

Tembine,

Tapo,

Danioko

et al. 2024

Preprint

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Section: Literature Reviewmentioning

confidence: 99%

Machine Intelligence in Africa: a survey

Tembine,

Tapo,

Danioko

et al. 2024

Preprint

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“…AI is a combination of algorithms to create machines that mimic human intelligence to perform tasks and can improve as they gather new information. AI is applicable to the diagnosis of infectious diseases including the detection of patients at risk of sepsis, the early detection of infections, the diagnosis of viral respiratory infections, and also as an aid in the radiological diagnosis of pulmonary tuberculosis [ 9 ]. One application of AI in clinical microbiology is the reading and interpretation of antibiograms using the disk diffusion method as described in the study of Pascucci M, et al [ 10 ].…”

Section: New Technologies Applied To Microbiological Diagnosticsmentioning

confidence: 99%

What are the most relevant publications in Clinical Microbiology in the last two years?

Cercenado

2023

Rev Esp Quimioter

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This minireview describes some of the articles published in the last two years related to innovative technologies including CRISPR-Cas, surface-enhanced Raman spectroscopy, microfluidics, flow cytometry, Fourier transform infrared spectroscopy, and artificial intelligence and their application to microbiological diagnosis, molecular typing and antimicrobial susceptibility testing. In addition, some articles related to resistance to new antimicrobials (ceftazidime-avibactam, meropenem-vaborbactam, imipenem-relebactam, and cefiderocol) are also described.

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“…These AI algorithms consider not only the quantity of data but also its quality and specificity, recognizing that accurate predictive models rely on accurate and relevant input data. The implementation of personalized malaria intervention systems through AI has the potential to significantly impact disease control in Africa [3,7]. By tailoring interventions to the specific needs of different regions, these systems can address existing challenges more effectively [8,9].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence (AI)-Based Solution to Malaria Fatalities In Africa: An Exploratory Review

Ogbaga¹

2023

Preprint

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Malaria remains a primary public health challenge in Africa, and there is growing interest in leveraging artificial intelligence (AI) to raise malaria interventions. This research examines the possible influence, challenges, and recommendations for implementing AI-based personalized malaria interventions in Africa. AI offers several opportunities in malaria management, including early detection and prediction of outbreaks, improved diagnosis, personalized interventions, optimal treatment recommendations, surveillance and response, resource optimization, and research innovation. However, the implementation of AI in malaria interventions faces various challenges. These include data availability and quality, infrastructure and resource constraints, contextual relevance and generalizability, ethical and privacy considerations, integration into healthcare workflows, and the need to build trust and acceptance among stakeholders. To address these challenges, it is recommended to strengthen data infrastructure, build local capacity in AI technologies, contextualize AI models to local settings, address ethical considerations, establish monitoring and evaluation frameworks, promote collaboration and knowledge sharing, and secure sustainable funding and long-term commitment. By considering these recommendations, stakeholders can work towards implementing AI-based personalized malaria interventions in Africa that can contribute to improving malaria control outcomes, reducing the weight of the disease, and advancing public health in the region.

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Scaling up artificial intelligence to curb infectious diseases in Africa

Cited by 9 publications

References 37 publications

Machine Intelligence in Africa: a survey

Machine Intelligence in Africa: a survey

What are the most relevant publications in Clinical Microbiology in the last two years?

Artificial Intelligence (AI)-Based Solution to Malaria Fatalities In Africa: An Exploratory Review

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