Understanding the Current and Potential Role of Artificial Intelligence in Healthcare

Clinical Question

How has artificial intelligence (AI) advanced healthcare, what are its current applications, and how must it be improved going forward?

Bottom Line

The use of AI in healthcare has the potential to improve clinical care and efficiency, accelerate research, and empower patients and communities, but challenges must be addressed.

Background: In its broadest sense, AI is a branch of computer science that aims to replace human intelligence using computer systems. This goal is achieved through sophisticated pattern recognition. AI has become increasingly significant in the realm of innovation in the healthcare industry in the last few years.

Study design: Literature review

Setting: King Fahad Medical City, Riyadh Second Health Cluster, Riyadh, Kingdom of Saudi Arabia

Synopsis: Referencing evidence from 11 studies, the author offers an overview of the current and future use of AI in healthcare. Currently, AI is predominantly used to enhance the pace and quality of care via algorithms to analyze and interpret medical imaging data. Subsets of AI, such as machine learning (ML) and deep learning (DL), have led to groundbreaking developments, with ML algorithms that can be converted to code and DL techniques able to provide early disease detection. Clinical decision support systems powered by AI have the potential to minimize human diagnostic errors, enhance decision‑making support, increase reproducibility, and assist physicians in the better use of data and documentation. Successful incorporation of AI into healthcare requires addressing two concepts: data with security and analytics with insights. One challenge of implementing AI involves the ethical implications of integrating AI technology, including concerns about privacy, consent, and autonomy. Also of note is the need for large amounts of high-quality data to ensure accurate AI analyses. One practical consideration is the challenge of integrating AI with an existing legacy system. The author emphasizes the need to raise the evidence threshold for AI applications when they extend to prediction, diagnosis, and treatment.

CITATION: Alhejaily AMG. Artificial intelligence in healthcare (review). Biomed Rep. 2024;22:11. doi:10.3892/br.2024.1889.

Comment: This review article explores the current healthcare applications of AI, focusing on complex data analysis, clinical decision support, and the enhancement of diagnostic accuracy. It covers applications such as medical imaging and personalized medicine, and also discusses ethical, regulatory, and integration challenges that must be addressed for effective adoption. Eric Gantwerker, MD