Exploring the role of artificial intelligence toward management of HIV and TB co-infection in Nigeria: a comprehensive narrative review.

IF 3.8 Q2 INFECTIOUS DISEASES
Therapeutic Advances in Infectious Disease Pub Date : 2025-11-24 eCollection Date: 2025-01-01 DOI:10.1177/20499361251395916
Umulkhairah Onyioiza Arama, Oluwatoyin Ayo-Farai, Mosunmade Oshingbesan, Bushra Murtaza, Sana Rasheed, Zareen Akhtar, Isaac Isiko, Abdullahi Adeyemi Adegoke, Bakare Sikiru Olayinka, Abdulkarim Surajo Abdulkarim, Malik Olatunde Oduoye
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引用次数: 0

Abstract

Human immunodeficiency virus (HIV) and tuberculosis (TB) co-infection in Nigeria are medical conditions of public health importance because they double the country's and its citizens' burden. Several management measures, including artificial intelligence (AI), are crucial for properly diagnosing and preventing these diseases. This study explores the role of AI in managing HIV and TB co-infection in Nigeria. A comprehensive literature search strategy was developed using the keywords "HIV," "TB," "co-infection," "artificial intelligence," and "Nigeria" across six electronic databases: PubMed, Google Scholar, Cochrane Library, Web of Science, ResearchGate, and African Journals Online. The review focused on articles published between January 2014 and December 2022 to capture recent advancements and trends in AI applications in managing HIV and TB co-infection. Approximately 23%-26% of people with HIV in Nigeria are infected with both TB and HIV. People living with HIV in Nigeria are 26 times more likely to develop TB due to their weakened immune systems. The Early Warning Outbreak Recognition Systems is an AI system used for TB detection that is in practice in Nigeria. However, findings showed that AI models, including deep learning, machine learning, Computer-aided detection, Fuzzy cognitive maps, and Logistic regressions, the Twin model could be helpful in the accurate management of HIV/TB co-infection in Nigeria compared to traditional models, for example, inaccurate classification of radiographs and detection of HIV drug resistance. Despite the importance of AI toward managing these diseases, Nigeria faces challenges, including the unavailability of skilled personnel and AI experts, and the poor quality of the IT infrastructure, which are barriers to integrating AI into healthcare in the country. Strategic collaboration between the Nigerian government, digital health agencies, and healthcare organizations is crucial to implementing AI effectively for the treatment of HIV and TB co-infection in Nigeria. By embracing AI, Nigeria can revolutionize its healthcare system, improve patient outcomes, and address public health challenges such as HIV and TB co-infection.

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探索人工智能在尼日利亚艾滋病毒和结核病合并感染管理中的作用:一项全面的叙述审查。
在尼日利亚,人类免疫缺陷病毒(HIV)和结核病(TB)合并感染是具有公共卫生重要性的医疗状况,因为它们使该国及其公民的负担加倍。包括人工智能(AI)在内的一些管理措施对于正确诊断和预防这些疾病至关重要。本研究探讨了人工智能在尼日利亚管理艾滋病毒和结核病合并感染中的作用。利用关键词“HIV”、“TB”、“合并感染”、“人工智能”和“尼日利亚”,在六个电子数据库(PubMed、谷歌Scholar、Cochrane Library、Web of Science、ResearchGate和African Journals Online)中制定了综合文献搜索策略。该审查侧重于2014年1月至2022年12月期间发表的文章,以了解人工智能应用在管理艾滋病毒和结核病合并感染方面的最新进展和趋势。尼日利亚约有23%-26%的艾滋病毒感染者同时感染了结核病和艾滋病毒。在尼日利亚,由于免疫系统较弱,艾滋病毒感染者患结核病的可能性是普通人的26倍。早期预警疫情识别系统是一种用于结核病检测的人工智能系统,目前正在尼日利亚实施。然而,研究结果表明,人工智能模型,包括深度学习、机器学习、计算机辅助检测、模糊认知图和Logistic回归,与传统模型(例如,不准确的x射线照片分类和艾滋病毒耐药性检测)相比,Twin模型可以帮助尼日利亚准确管理艾滋病毒/结核病合并感染。尽管人工智能对管理这些疾病很重要,但尼日利亚面临着挑战,包括缺乏熟练人员和人工智能专家,以及IT基础设施质量差,这些都是将人工智能纳入该国医疗保健的障碍。尼日利亚政府、数字卫生机构和卫生保健组织之间的战略合作对于在尼日利亚有效实施人工智能治疗艾滋病毒和结核病合并感染至关重要。通过采用人工智能,尼日利亚可以彻底改变其医疗保健系统,改善患者的治疗效果,并应对艾滋病毒和结核病合并感染等公共卫生挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.30
自引率
8.80%
发文量
64
审稿时长
9 weeks
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