Large language models

Large language models are advanced artificial intelligence systems designed to understand and generate human-like text. These models are built using deep learning techniques and are trained on vast amounts of text data, such as books, articles, and websites. Large language models utilize algorithms like transformers to process and understand the relationships between words and sentences ¹.

The primary function of the large language model is natural language processing (NLP), which involves tasks like language generation, language translation, sentiment analysis, question answering, and text summarization. Large language models are capable of understanding context, grammar, and semantics, enabling them to generate coherent and contextually appropriate responses.

However, it is important to note that while large language models are powerful tools, they have limitations. They lack common sense reasoning and may generate incorrect or biased responses if not properly guided. Ethical considerations, data privacy, and responsible deployment of large language models are important factors to consider when utilizing these models in real-world applications.

Transformer

Transformers are a type of neural network architecture that has gained significant popularity in NLP tasks. The transformer architecture revolves around the concept of attention mechanisms, which allow the model to focus on different parts of the input sequence when making predictions or generating output ². 

Application of large language models in radiology

• radiology report generation: large language models can assist in generating radiology reports by using keywords as input ³

• automated image annotation: large language models can be utilized to automatically annotate medical images with relevant information ^ref

• clinical decision support

  • large language models can process patient history, medical imaging data, and relevant literature to provide recommendations for diagnosis, treatment planning, or follow-up suggestions ^ref

  • large language models can assist radiologists in making more informed decisions by providing access to a vast amount of medical knowledge and evidence ^ref

• LNP for radiology: large language models can be employed for extracting relevant information from radiology reports, analyzing clinical text data, or assisting in medical coding and billing processes ^ref