Preliminary analysis of AI-based thyroid nodule evaluation in a non-subspecialist endocrinology setting.

Journal: Endocrine
Published Date: Jun 5, 2025

Abstract

PURPOSE: Thyroid nodules are commonly evaluated using ultrasound-based risk stratification systems, which rely on subjective descriptors. Artificial intelligence (AI) may improve assessment, but its effectiveness in non-subspecialist settings is unclear. This study evaluated the impact of an AI-based decision support system (AI-DSS) on thyroid nodule ultrasound assessments by general endocrinologists (GE) without subspecialty thyroid imaging training.

Authors

  • Pablo Fernández Velasco
    Department of Endocrinology and Nutrition, Hospital Clínico Universitario Valladolid, Valladolid, Spain. pablo.fernandez.velasco@estudiantes.uva.es.
  • Lucia Estévez Asensio
    Department of Endocrinology and Nutrition, Hospital Clínico Universitario Valladolid, Valladolid, Spain.
  • Beatriz Torres
    Department of Endocrinology and Nutrition, Hospital Clínico Universitario Valladolid, Valladolid, Spain.
  • Ana Ortolá
    Department of Endocrinology and Nutrition, Hospital Clínico Universitario Valladolid, Valladolid, Spain.
  • Emilia Gómez Hoyos
    Department of Endocrinology and Nutrition, Hospital Clínico Universitario Valladolid, Valladolid, Spain.
  • Esther Delgado
    Department of Endocrinology and Nutrition, Hospital Clínico Universitario Valladolid, Valladolid, Spain.
  • Daniel de Luis
    Center of Investigation of Endocrinology and Clinical Nutrition, Medicine School, Department of Endocrinology and Nutrition Hospital Clinico Universitario, University of Valladolid, Valladolid Spain. Electronic address: dadluis@yahoo.es.
  • Gonzalo Díaz Soto
    Department of Endocrinology and Nutrition, Hospital Clínico Universitario Valladolid, Valladolid, Spain.

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