Although chatbots have existed for decades, the emergence of transformer-based large
language models (LLMs) has captivated the world through the most recent wave of artificial …

Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to
a readily accessible tool for cancer researchers. AI-based tools can boost research …

Large language models (LLMs) have shown potential in various applications, including
clinical practice. However, their accuracy and utility in providing treatment recommendations …

Abstract The advent of Deep Learning (DL) has significantly propelled the field of diagnostic
radiology forward by enhancing image analysis and interpretation. The introduction of the …

To start, we need more rigorous testing of algorithms with prospective, pragmatic, real-world
clinical trials in diverse settings to assure robust generalizability, lack of biases, and a high …

Liver cancer has high incidence and mortality globally. Artificial intelligence (AI) has
advanced rapidly, influencing cancer care. AI systems are already approved for clinical use …

Multimodal artificial intelligence (AI) systems have the potential to enhance clinical decision-
making by interpreting various types of medical data. However, the effectiveness of these …

Background Pretraining labeled datasets, like ImageNet, have become a technical standard
in advanced medical image analysis. However, the emergence of self-supervised learning …

Eric Topol is founder and director of the Scripps Research Translational Institute, a professor
of molecular medicine, and executive vice-president of Scripps Research. He has published …

Editor: We read with great interest the retrospective study by Dr Khader and colleagues (1),
published in the October 2023 issue of Radiology. Their transformer-based deep learning …