Large language model GPT-4 matched the performance of radiologists in detecting errors in radiology reports, according to research published in Radiology, a journal of the Radiological Society of North America (RSNA).

Errors in radiology reports may occur due to resident-to-attending discrepancies, speech recognition inaccuracies and high workload. Large language models, such as GPT-4, have the potential to enhance the report generation process.

Current Artificial Intelligence (AI) models for cancer treatment are trained and approved only for specific intended purposes. GMAI models, in contrast, can handle a wide range of medical data including different types of images and text. For example, for a patient with colorectal cancer, a single GMAI model could interpret endoscopy videos, pathology slides and electronic health record (EHR) data. Hence, such multi-purpose or generalist models represent a paradigm shift away from narrow AI models.

Investigators have applied artificial intelligence (AI) techniques to gait analyses and medical records data to provide insights about individuals with leg fractures and aspects of their recovery.

The study, published in the Journal of Orthopaedic Research, uncovered a significant association between the rates of hospital readmission after fracture surgery and the presence of underlying medical conditions.

Researchers at the National Institutes of Health applied artificial intelligence (AI) to a technique that produces high-resolution images of cells in the eye. They report that with AI, imaging is 100 times faster and improves image contrast 3.5-fold. The advance, they say, will provide researchers with a better tool to evaluate age-related macular degeneration (AMD) and other retinal diseases.

The same class of artificial intelligence that made headlines coding software and passing the bar exam has learned to read a different kind of text - the genetic code.

That code contains instructions for all of life's functions and follows rules not unlike those that govern human languages. Each sequence in a genome adheres to an intricate grammar and syntax, the structures that give rise to meaning.

Implementing a single shared digital prescribing record across the NHS in England could avoid nearly 1 million drug errors every year, stopping up to 16,000 fewer patients from being harmed, and saving up to 22 lives every year, suggests a modelling study, published online in BMJ Quality & Safety.

When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations and can sometimes generate incorrect advice or instructions. A new study in the American Journal of Preventive Medicine, published by Elsevier,