Artificial Intelligence and Endocrine Radiology
PDF
Cite
Share
Request
Review
E-PUB
18 November 2025

Artificial Intelligence and Endocrine Radiology

Turk Radiol Semin. Published online 18 November 2025.
No information available.
No information available
Received Date: 28.09.2025
Accepted Date: 30.10.2025
E-Pub Date: 18.11.2025
PDF
Cite
Share
Request

ABSTRACT

Endocrine radiology is a broad field that encompasses many subspecialties of radiology, ranging from neuroradiology to abdominal radiology. In recent years, rapid advances in information processing hardware and, in particular, deep learning methods have led to artificial intelligence research and applications, triggering rapid changes in radiology. In parallel, various scientific institutions and organizations around the world have published numerous guidelines and resources. In this context, it is emphasized that the focus should be on the power of artificial intelligence to create new opportunities, describing it as a “game changer,” and ensuring its ethical use with patient benefit in mind. Radiology is at the forefront of artificial intelligence in the health discipline. In addition to scientific research on artificial intelligence in medical imaging, there are numerous Conformité Européenne and Food and Drug Administration approved artificial intelligence products used in daily practice. These applications have the potential to transform diagnostic processes by increasing accuracy in image interpretation. There are also many areas in endocrine radiology where artificial intelligence can be utilized. Within these areas, thyroid nodules and pituitary adenomas are currently at the forefront. Parathyroid adenomas, adrenal glands, and neuroendocrine tumors are other areas being studied. This article discusses the general status of artificial intelligence in radiology, specific artificial intelligence applications in endocrine system imaging, ethical and legal dimensions, and future projections.

Keywords:
Artificial intelligence, endocrine, medical imaging