The Transformative Role of Artificial Intelligence in Non-Communicable Disease Management
Non-communicable diseases (NCDs), encompassing chronic conditions such as cardiovascular diseases, cancer, diabetes, and chronic respiratory diseases, represent a substantial and escalating burden on global public health and healthcare systems, accounting for nearly 74% of all global deaths. The timely identification and risk assessment of NCDs are crucial for improving patient outcomes, reducing complications, extending life expectancy, and alleviating the significant economic strain on healthcare systems. However, late-stage diagnoses continue to pose significant challenges, leading to limited treatment options, poorer prognoses, and increased healthcare costs.
In response to these challenges, artificial intelligence (AI) is emerging as a transformative force that can reshape healthcare by analyzing vast datasets, identifying patterns, and generating actionable insights, making it a critical ally in early NCD detection and risk assessment. AI-driven algorithms excel in various healthcare applications, from medical imaging and predictive analytics to personalized medicine, offering the promise of earlier and more accurate diagnoses, improved risk stratification, and timely interventions.
A comprehensive bibliometric study by Al-Dekah and Sweileh (2025) systematically analyzes the evolving landscape of AI solutions for NCDs, shedding light on its current state, emerging trends, and future clinical potential. The study, which retrieved 1745 relevant articles from the Scopus database published between 2000 and 2024, reveals a notable surge in research activity in recent years, indicating a thriving and dynamic research landscape in this area. Findings highlight the increasing role of AI in early detection and risk prediction of NCDs, emphasizing its widening research impact.
Key research hotspots identified include:
- Machine learning and deep learning, signifying the most common AI approaches.
- Specific NCDs such as Alzheimer’s disease, breast cancer, and diabetes, indicating areas of intense focus for AI application.
- Research themes like risk prediction, early diagnosis, and medical imaging, which underscore the practical applications of AI in improving patient care.
The analysis also emphasizes the importance of international research collaboration, with countries like China, the USA, India, the UK, and Saudi Arabia leading contributions and demonstrating robust partnerships in advancing this field. The substantial growth in citations further signals the widespread recognition and impact of AI in NCD management. This research provides invaluable insights for informing decision-making, fostering interdisciplinary collaboration, and enhancing patient care and resource allocation in the context of NCDs.
Reference for the article:
Al-Dekah, A. M., & Sweileh, W. (2025). Role of artificial intelligence in early identification and risk evaluation of non-communicable diseases: a bibliometric analysis of global research trends. BMJ Open, 15, e101169. https://doi.org/10.1136/bmjopen-2025-101169