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

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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