At the world’s foremost radiology conference, new applications for artificial intelligence (AI) showed promise to alleviate radiologists’ unsustainable workloads and improve the efficiency of disease screening.
The Radiological Society of North America (RSNA) held its annual meeting, historically one of the medical community’s largest, this past November in Chicago. On the upper levels of McCormick Place, academics in the field of radiology shared findings and updates, while below, the exhibition floor buzzed with salespeople and brand ambassadors from dozens of vendors amid a sea of potential customers. Products and services built around AI were ubiquitous and diverse, so much so that one of two showcase theaters, stages on the exhibition floor where representatives gave brief presentations about their companies, was dedicated to AI. Nearly every presenter brought up the need to employ AI technology to address the discrepancy between the volume of cases requiring radiologist attention and what they can actually manage before experiencing burnout.
Applications ran the gamut from musculoskeletal health to cardiovascular, neurological, and beyond. A more recently developed subset of AI platforms, large language models (LLMs) such as OpenAI’s GPT 3.5 and 4.0, are capable of understanding and generating human-like content through text prompts. LLMs demonstrate impressive performance and can be highly useful for administrative and documenting tasks such as generating reports, translating messages, and serving as chatbots for support. At this stage, however, there may be greater immediate clinical value in software that allows radiologists to do more with their time and resources to help more patients than they could on their own. Below are three companies working to make radiology more efficient and, ultimately, improve patient outcomes with strategic AI.