The use of artificial intelligence in healthcare to promote sustainable development goals: a bibliometric review and a future research and policy agenda

Context: The United Nations' Sustainable Development Goals (SDGs) see health as the protagonist of SDG #3, which is designed to guarantee the health of all individuals. Innovative solutions are required to reach the goal, as many barriers are present, also following the outcomes of the COVID-19 pandemic. The current literature agrees that technologies such as Artificial intelligence (AI), the Internet of Things, Virtual Reality, and Big Data Analytics offer promising opportunities to improve healthcare delivery and support achieving SDGs' objectives. When it comes to AI, literature underlines a gap in comprehending its actual impact on healthcare and contribution to the SDGs. Method: This study aims to address such a gap by conducting a bibliometric analysis on Scopus, the largest scientific dataset. More in detail, emphasis was placed on articles labelled under the disciplines of business management and medicine, addressing the implications of AI-based healthcare applications and their impact on the SDGs. The initial queries produced 5,300 results, which were subsequently refined to a final sample of 1,020 articles through systematic filtering and abstract screening. The software Leximancer was employed to analyse results and identify critical themes and clusters associated with the role of AI in healthcare. Results: Five primary clusters of AI applicability in healthcare were identified. The initial cluster underscored the importance of AI in enhancing healthcare systems and decision-making processes, emphasizing the importance of collaboration between human healthcare providers and AI tools. The second cluster concentrated on women's health, with AI assisting in identifying gender-specific hazards and developing customized interventions. A third cluster was established to investigate diagnostic innovations, which involve improving medical diagnoses through machine learning and deep learning algorithms. The fourth cluster deepened the social determinants of health, illustrating how AI can mitigate disparities by analysing socioeconomic factors. The fifth cluster focused on the role of AI during the COVID-19 pandemic, illustrating its potential for outbreak prediction, resource optimization, and vaccine development. Discussion: As a result, AI's integration into healthcare is consistent with SDG #3 and its associated objectives, including the reduction of health inequalities and the enhancement of universal health coverage. It also promotes equitable access to healthcare and addresses gender-specific health requirements, thereby supporting other SDGs, such as SDG #5 (Gender Equality) and SDG #10 (Reduced Inequalities). Future research should concentrate on the personalization of AI models, the mitigation of biases, and ethical AI implementation. Therefore, healthcare professionals should be trained to effectively utilize AI tools to optimize their benefits and improve healthcare outcomes. These endeavours will make a substantial contribution to the realization of SDG #3 and the promotion of a global health system that is both sustainable and equitable.