Role of artificial intelligence in acromegaly detection and management

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Abstract
Despite significant advances in the diagnosis and treatment of acromegaly, diagnostic delay remains substantial, often exceeding 6 to 10 years, while a significant proportion of patients remain inadequately controlled despite multiple available therapeutic modalities. Artificial intelligence (AI) is a promising tool to address several challenges across the acromegaly care pathway, from early disease detection to individualized treatment selection and outcome prediction. AI-assisted facial and hand image analysis has demonstrated the potential to identify subtle phenotypic changes and reduce diagnostic delay, facilitating earlier recognition of the disease. In parallel, machine learning and deep learning approaches have been increasingly employed to predict surgical remission, response to medical therapy, and radiotherapy outcomes, often outperforming individual biomarkers. AI models further support the development of precision medicine strategies capable of improving patient stratification and therapeutic decision-making. This review summarizes current and emerging applications of AI in acromegaly, including facial recognition technologies, radiomics, and machine-learning predictive models integrating clinical, biochemical, radiological, and molecular data.

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