AI-enhanced telemedicine for personalized antiretroviral therapy in HIV patients with neurological comorbidities: a narrative review.

Abstract

Background: Human immunodeficiency virus (HIV), while now manageable as a chronic health condition with highly active antiretroviral therapy (HAART), often precipitates the onset of neurological comorbidities such as HIV-associated neurocognitive disorders (HAND) and a number of neuropathies. ART, though effective, may lead to neurotoxic adverse drug reactions, impacting patient adherence and clinical outcomes. Innovative approaches are warranted to balance ART efficacy with minimized neurological risk.

Objective: This paper investigates how artificial intelligence (AI) may improve telemedicine for individualized ART management to reduce neurotoxicity and raise patient adherence to medication regimes.

Methods: A comprehensive literature review was conducted using PubMed/MEDLINE, and Google Scholar, among other electronic search databases, with keywords comprising "Artificial Intelligence," "Telemedicine," "HIV," and "Neurological Comorbidities." Studies were selected based on relevance to AI applications in personalized HIV care. Inclusion criteria included peer-reviewed articles, systematic reviews, and clinical trials on AI in HIV care. Exclusion criteria omitted non-peer-reviewed articles and studies lacking direct AI relevance. Titles and abstracts were screened before full-text review.

Results: There is potential for individualized ART management with AI-integrated telemedicine. By anticipating clinical concerns pertaining to ART-associated neurotoxicity, machine learning systems allow for preemptive therapeutic modifications. Wearable technology and AI-powered mHealth apps enable real-time adherence and symptom monitoring, facilitating the prompt adjustments to therapy if necessitated whilst lowering neurotoxic adverse drug reactions.

Conclusions: AI-enhanced telemedicine promotes customized ART regimens that bolster clinical outcomes and individual quality of life, providing a revolutionary approach to HIV management in populations affected by neurological sequalae. In order to provide fully personalized HIV care, future research should concentrate on improving AI model accuracy across a range of demographics while tackling moral issues pertaining to patient confidentiality and data privacy.