Artificial intelligence (AI) continues to make significant strides in various industries, and its integration into healthcare is particularly promising. However, a recent study by Osaka Metropolitan University evaluated the diagnostic abilities of generative AI models, specifically ChatGPT, in
The FDA has recently cleared a breakthrough in cardiac diagnostic technology: AISAP Cardio's AI-powered point-of-care ultrasound (POCUS) software platform. Developed by the Israeli healthcare technology company AISAP, this new software is specifically designed to diagnose structural heart diseases
In a significant development reflecting the rapid advancements in artificial intelligence (AI) technology, the U.S. Food and Drug Administration (FDA) has recently added a substantial number of AI and machine learning-enabled medical products to its list of approved clinical AI applications. With
The field of radiology stands at the forefront of medical innovations that facilitate improved healthcare delivery. Artificial Intelligence (AI) has emerged as a transformative force within this domain, promising enhanced diagnostic accuracy and efficiency. However, the pressing question remains:
The advent of artificial intelligence (AI) in medical diagnostics has promised significant advancements in healthcare delivery, particularly through the analysis of medical images such as chest X-rays. However, the development and deployment of these AI systems also raise crucial concerns about
The article, published in Academic Radiology, examines the potential of large language models (LLMs) such as ChatGPT (specifically GPT-4) and Llama 2 in crafting educational materials and board-style questions for radiology. These models were tested on their ability to produce multiple-choice
