Toward artificial general intelligence in health care

Toward artificial general intelligence in health care

연구 분야: Artificial Intelligence

학회: The Visual Computer

Artificial intelligence (AI) has seen remarkable advancements across various fields, with health care emerging as a particularly promising area. The integration of AI in health care has evolved from early symbolic systems to advanced foundation and generative models, profoundly enhancing disease diagnosis and personalized medicine as reported (Feng et al. How Far Are We From AGI, arXiv:2405.10313, 2024). This paper provides a comprehensive review of the evolution of AI in health care, focusing on the transition from narrow AI to artificial general intelligence (AGI). AGI, a hypothetical form of AI possessing human-level intelligence, is envisioned to perform any intellectual task. Unlike narrow AI, which is task-specific, AGI demonstrates broad cognitive abilities, enabling it to adapt to diverse tasks and scenarios. This paper explores the characteristics of previous and current AI models in health care, highlights their limitations, and discusses the potential role of AGI in bridging uniformity gaps and fostering global medical collaboration. While acknowledging the ethical, technological, and societal challenges associated with this shift, the paper aims to set the stage for nuanced discussions on the future of AGI in health care. By critically examining the potential of AGI to handle complex and heterogeneous data, generalize knowledge across domains, and provide personalized care, this paper contributes to the ongoing debate on the role of AI in transforming healthcare delivery.