The evolution of health in science: future perspectives

Abstract

This editorial discusses the future perspectives of artificial intelligence in healthcare delivery, research, and education, highlighting its potential to integrate multiple sources of information, support clinical decision-making, personalize care, and broaden access to advanced healthcare technologies. Challenges related to data quality and representativeness, algorithmic bias, interoperability, model transparency, legal accountability, and the continuous monitoring of artificial intelligence systems following implementation are also discussed. Furthermore, the editorial emphasizes the importance of using artificial intelligence to automate administrative processes, enabling healthcare professionals—particularly nurses—to devote more time to direct patient care, communication, and the establishment of therapeutic relationships. In professional education, it underscores the need to develop digital competencies without compromising the acquisition of independent clinical reasoning, drawing attention to the potential risk of never-skilling. Finally, the editorial examines the growing adoption of predictive technologies, multimodal models, biosensors, and digital health applications, reinforcing the urgent need for robust frameworks for governance, regulation, and clinical validation. It concludes that the impact of artificial intelligence on healthcare will depend on successfully integrating technological innovation with ethical principles, equity, transparency, and social responsibility, ensuring that scientific advances translate into meaningful improvements for both individuals and populations.