Radiological Differential Diagnoses Based on Cardiovascular and Thoracic Imaging Patterns: Perspectives of Four Large Language Models

Abstract

Background Differential diagnosis in radiology is a critical aspect of clinical decision-making. Radiologists in the early stages may find difficulties in listing the differential diagnosis from image patterns. In this context, the emergence of large language models (LLMs) has introduced new opportunities as these models have the capacity to access and contextualize extensive information from text-based input.

Keywords

• artificial intelligence
• cardiothoracic
• ChatGPT
• Google Bard
• Microsoft Bing
• perplexity
• differential diagnosis
• radiologists