BACKGROUND: Large language models (LLMs) such as ChatGPT have rapidly revolutionized the way computers can analyze human language and the way we can interact with computers.
BACKGROUND: The rapid development of large language models (LLMs) opens up new possibilities for the automated processing of medical texts. Transforming unstructured radiology reports into structured data is crucial for efficient use in clinical deci...
CLINICAL/METHODICAL ISSUE: Artificial intelligence (AI) is being increasingly integrated into clinical practice. However, the specific benefits are still unclear to many users.
BACKGROUND: Due to the ongoing rapid advancement of artificial intelligence (AI), including large language models (LLMs), radiologists will soon face the challenge of the responsible clinical integration of these models.
BACKGROUND: The medical coding of radiology reports is essential for a good quality of care and correct billing, but at the same time a complex and error-prone task.
BACKGROUND: Mammography screening programs (MSP) have shown that breast cancer can be detected at an earlier stage enabling less invasive treatment and leading to a better survival rate. The considerable numbers of interval breast cancer (IBC) and th...
CLINICAL-METHODOLOGICAL PROBLEM: Imaging procedures employing ionizing radiation require compliance with European directives and national regulations in order to protect patients. Each exposure must be indicated, individually adapted, and documented....