Generative Artificial Intelligence in Clinical Medicine and Impact on Gastroenterology.

Abstract

The pace of artificial intelligence (AI) integration into health care has accelerated with rapid advances in generative AI (genAI). Gastroenterology and hepatology in particular will be transformed due to the multimodal workflows that integrate endoscopic video, radiologic imaging, tabular data, and unstructured note text. GenAI will impact the entire spectrum of clinical experience, from administrative tasks, diagnostic guidance, and treatment recommendations. Unlike traditional machine learning approaches, genAI is more flexible, with one platform able to be used across multiple tasks. Initial evidence suggests benefits in lower-level administrative tasks, such as clinical documentation, medical billing, and scheduling; and information tasks, such as patient education and summarization of the medical literature. No evidence exists for genAI solutions for more complex tasks relevant to clinical care, such as clinical reasoning for diagnostic and treatment decisions that may affect patient outcomes. Challenges of output reliability, data privacy, and useful integration remain; potential solutions include robust validation, regulatory oversight, and "human-AI teaming" strategies to ensure safe, effective deployment. We remain optimistic in the potential of genAI to augment clinical expertise due to the adaptability of genAI to handle multiple data modalities to obtain and focus relevant information flows and the human-friendly interfaces that facilitate ease of use. We believe that the potential of genAI for dynamic human-algorithmic interactions may allow for a degree of clinician-directed customization to enhance human presence.