Impact and Challenges of Artificial Intelligence Integration in the African Health Sector: A Review

Trends in Medical Research, Год журнала: 2024, Номер 19(1), С. 220 - 235

Опубликована: Июнь 11, 2024

Artificial intelligence has proven to be a game-changing force in health sectors throughout Africa offering prospects for significant development.In sub-Saharan Africa, using AI healthcare, especially areas with limited resources, holds valuable promise transforming and improving healthcare.This article takes an excellent look at how is being integrated into the African sector, as well examining policy frameworks, challenges future possibilities.This begins by giving overview of highlighting groundbreaking impact technologies combating addressing healthcare that occur within countries.Ranges from mobile-based diagnostics precision medicine, artificial its potential capabilities diagnosing, treating operations providing solutions resource constraints accessibility challenges.However, despite these advancements, there are still obstacles such infrastructure limitations, concerns about data privacy gaps professionals' training hinder realization AI's envisions where adoption fully incorporated community initiatives enhanced access services betterment across countries.While barriers like unequal persist, need governments stakeholders prioritize digital catalysts sector Africa.

Язык: Английский

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Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing

Parasites & Vectors, Год журнала: 2025, Номер 18(1)

Опубликована: Янв. 29, 2025

Abstract Background Amebiasis represents a significant global health concern. This is especially evident in developing countries, where infections are more common. The primary diagnostic method laboratories involves the microscopy of stool samples. However, this approach can sometimes result misinterpretation amebiasis as other gastroenteritis (GE) conditions. goal work to produce machine learning (ML) model that uses laboratory findings and demographic information automatically predict amebiasis. Method Data extracted from Jordanian electronic medical records (EMR) between 2020 2022 comprised 763 amebic cases 314 nonamebic cases. Patient demographics, clinical signs, microscopic diagnoses, leukocyte counts were used train eight decision tree algorithms compare their accuracy predictions. Feature ranking correlation methods implemented enhance classifying Results dependent variables distinguishing include percentage neutrophils, mucus presence, red blood cells (RBCs) white (WBCs) Prediction precision ranged 92% 94.6% when employing classifiers including (DT), random forest (RF), XGBoost, AdaBoost, gradient boosting (GB). optimized RF demonstrated an area under curve (AUC) 98% for detecting data, utilizing only 300 estimators with max depth 20. study highlights concern Jordan, responsible 17.22% all episodes study. Male sex age associated higher incidence ( P = 0.014), over 25% occurring infants toddlers. Conclusions application ML EMR accurately finding significantly contributes emerging use support system parasitic disease diagnosis. Graphical

Язык: Английский

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Building Trustworthiness as a Requirement for AI in Africa: Challenges, Stakeholders and Perspectives

Опубликована: Янв. 1, 2025

Abstract As Africa embraces the potential of Artificial Intelligence (AI) for socio-economic development, continent faces unique challenges and opportunities in building a trustworthy sovereign AI ecosystem. While several African nations, led by Mauritius 2018, have launched national strategies, must navigate complex dynamics, including digital divide risk colonialism. The reliance on foreign solutions can undermine Africa's autonomy perpetuate dependency, making it crucial to prioritise locally developed technologies that align with continent's cultural realities. Union other international initiatives laid groundwork responsible deployment, emphasising ethics, inclusivity local sovereignty. However, success hinges active engagement diverse stakeholders, governments, educational institutions, private sector entities, communities multilateral organisations. These stakeholders collaborate create an ecosystem fosters innovation, upholds ethical standards mitigates risks external dependency investing homegrown solutions. Governments play role establishing regulatory frameworks, promoting public-sector applications forming strategic partnerships. Simultaneously, institutions are essential cultivating talent driving research, while contribute vitality. Ensuring inclusive, adaptive resilient will require ongoing collaboration trust-building among all parties. Ultimately, vibrant, self-regulated position as leader global governance, harnessing technology sustainable development safeguarding its

Язык: Английский

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Diagnosis and Management of Sexually Transmitted Infections Using Artificial Intelligence Applications Among Key and General Populations in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

Algorithms, Год журнала: 2025, Номер 18(3), С. 151 - 151

Опубликована: Март 7, 2025

The Fourth Industrial Revolution (4IR) has significantly impacted healthcare, including sexually transmitted infection (STI) management in Sub-Saharan Africa (SSA), particularly among key populations (KPs) with limited access to health services. This review investigates 4IR technologies, artificial intelligence (AI) and machine learning (ML), that assist diagnosing, treating, managing STIs across SSA. By leveraging affordable accessible solutions, tools support KPs who are disproportionately affected by STIs. Following systematic guidelines using Covidence, this study examined 20 relevant studies conducted SSA countries, Ethiopia, South Africa, Zimbabwe emerging as the most researched nations. All reviewed used secondary data favored supervised ML models, random forest XGBoost frequently demonstrating high performance. These tracking services, predicting risks of STI/HIV, developing models for community HIV clusters. While AI enhanced accuracy diagnostics efficiency management, several challenges persist, ethical concerns, issues quality, a lack expertise implementation. There few real-world applications or pilot projects Notably, primarily focus on development, validation, technical evaluation methods rather than their practical application As result, actual impact these approaches point care remains unclear. highlights effectiveness various through detection, diagnosis, treatment, monitoring. strengthens knowledge technologies Understanding potential improve sexual outcomes, address gaps STI surpass limitations traditional syndromic approaches.

Язык: Английский

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Machine learning evidence towards eradication of malaria burden: A scoping review

Applied Computer Science, Год журнала: 2025, Номер 21(1), С. 44 - 69

Опубликована: Март 31, 2025

Recent advancements have shown that shallow and deep learning models achieve impressive performance accuracies of over 97% 98%, respectively, in providing precise evidence for malaria control diagnosis. This effectiveness highlights the importance these enhancing our understanding management, which includes critical areas such as control, diagnosis economic evaluation burden. By leveraging predictive systems models, significant opportunities eradicating malaria, empowering informed decision-making facilitating development effective policies could be established. However, global burden is approximated at 95%, there a pressing need its eradication to facilitate achievement SDG targets related good health well-being. paper presents scoping review covering years 2018 2024, utilizing PRISMA-ScR protocol, with articles retrieved from three scholarly databases: Science Direct (9%), PubMed (41%), Google Scholar (50%). After applying exclusion inclusion criteria, final list 61 was extracted review. The results reveal decline research on machine techniques while steady increase approaches has been noted, particularly volume dimensionality data continue grow. In conclusion, clear utilize algorithms through real-time collection, model development, deployment evidence-based recommendations Future directions should focus standardized methodologies effectively investigate both models.

Язык: Английский

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Knowledge as the Engine: Transforming Healthcare Delivery Through Information and Communications Technology Applying a Sustainable Development Framework

Sustainable Development, Год журнала: 2025, Номер unknown

Опубликована: Апрель 7, 2025

ABSTRACT The future of health in Ghana is indeed a complex and multifaceted landscape characterized by both challenges promising opportunities. Such opportunities lie adopting technology, which can revolutionize healthcare knowledge management elevate quality Ghana. As such, this study tested the prognosis using lens technology acceptance model (TAM) to investigate information communications (ICT) assimilation activities (KA) improve delivery Community‐based Health Planning Services (CHPS) zones TAM framework offers strong theoretical basis for evaluating professionals' use ICT providing services. A pooled dataset 657 sector respondents was employed test hypothesis Partial Least Squares Structural Equation Modeling (PLS‐SEM) technique. It found that adoption KA significantly helps facilities Moreover, relationship best mediated through policies (HP) KA. results further demonstrate effective CHPS contributes HP monitoring. concluded advent has reformed collaboration among diverse teams sector, fostering seamless exchange expertise. This interactive platform, accessible at fraction cost traditional methods, empowers providers work together effectively, enhancing efficiency patient care.

Язык: Английский

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A Machine Learning-Based Web Application for Heart Disease Prediction

Intelligent Control and Automation, Год журнала: 2024, Номер 15(01), С. 9 - 27

Опубликована: Янв. 1, 2024

This work leveraged predictive modeling techniques in machine learning (ML) to predict heart disease using a dataset sourced from the Center for Disease Control and Prevention US. The was preprocessed used train five models: random forest, support vector machine, logistic regression, extreme gradient boosting light boosting. goal use best performing model develop web application capable of reliably predicting based on user-provided data. classifier provided most reliable results with precision, recall F1-score 97%, 72%, 83% respectively Class 0 (no disease) 21% (precision), 81% (recall) 34% (F1-score) 1 (heart disease). further deployed as application.

Язык: Английский

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The Strategic Efficacy of Artificial Intelligence (AI) in Medical Tourism

Advances in hospitality, tourism and the services industry (AHTSI) book series, Год журнала: 2024, Номер unknown, С. 99 - 138

Опубликована: Март 18, 2024

AI's integration and adoption in the sector have evolved to be a game-changer through operational revolutionisation regarding accessibility advanced diagnosis treatments, reduced waiting times, cost savings. This chapter explores strategic efficacy of AI context medical tourism. Using term “strategic efficacy,” authors encompass concept efficiency effectiveness achieving outcome The authors' purviews are that is important ensure an strategy tourism not only looks good on paper but also continues produce high success for global practice. In this chapter, discuss emergence industry, tourism, categories AI-system devices used devices. Also discussed systems applications some major diseases

Язык: Английский

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Determinants of under-five mortality in Zimbabwe: Evidence from the 2015–2016 Zimbabwe demographic Health Survey data

Women and Children Nursing, Год журнала: 2024, Номер 2(1), С. 1 - 8

Опубликована: Март 1, 2024

Child mortality is an important measure of a population's health status. It included in the third sustainable development goal that aims to improve global by reducing under-five at least as low 25 per 1000 live births 2030. The study determines factors associated with child Zimbabwe. Cross-sectional secondary data from 2015 Zimbabwe Demographic Health Survey (ZDHS) were analyzed. sample 5806 women aged 15–49 years reproductive age. Chi-square test was used analyze association between death and independent variables. We identified individual contextual deaths using Cox proportional hazard model. risks highest among children first birth order (adjusted ratio (aHR) = 2.37, P 0.04), multiple (aHR P=0.04), mothers primary or less maternal education 1, Ref), below 18 old apostolic 2.90, P=0.002), who do not use contraceptives 2.20, < 0.001), formerly married 6.42, P=0.005), 5 more 15.84, read newspapers than once week 1.75, P=0.13), households high-polluting fuels 1.92, P=0.023). This establishes health, maternal, socioeconomic, household, ecological are determinants Understanding these crucial for designing effective interventions policies reduce rates. requires comprehensive approaches such improving access healthcare, education, basic sanitation facilities; prioritizing nutrition; providing clean water; enhancing poverty reduction immunization; promoting breastfeeding social empowerment, particular focus on vulnerable populations marginalized communities.

Язык: Английский

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Evolving Conversations: A Review of Chatbots and Implications in Natural Language Processing for Cultural Heritage Ecosystems

International Journal of Robotics and Control Systems, Год журнала: 2023, Номер 3(4), С. 955 - 1006

Опубликована: Дек. 5, 2023

Chatbot technology, a rapidly growing field, uses Natural Language Processing (NLP) methodologies to create conversational AI bots. Contextual understanding is essential for chatbots provide meaningful interactions. Still, date often struggle accurately interpret user input due the complexity of natural language and diverse fields, hence need Systematic Literature Review (SLR) investigate motivation behind creation chatbots, their development procedures methods, notable achievements, challenges emerging trends. Through application PRISMA method, this paper contributes revealing rapid dynamic progress in chatbot technology with NLP learning models, enabling sophisticated human-like interactions on trends observed over past decade. The results, from various fields such as healthcare, organization business, virtual personalities, education, do not rule out possibility being developed other cultural preservation while suggesting supervision aspects comprehension bias ethics users. In end, insights gained SLR have potential contribute significantly advancement comprehensive field.

Язык: Английский

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