The Liver Imaging Reporting and Data System version 2018 treatment response algorithm performs well for lesions treated with ablation when observations are assessed on MRI as viable or nonviable di... Background The Liver Imaging Reporting and Data System (LI-RADS) treatment response algorithm (TRA) is used to assess presumed hepatocellular carcinoma (HCC) after local-regional therapy, but its p...

Artificial intelligence (AI) has been a topic of substantial interest for radiologists in recent years. Although many of the first clinical applications were in the neuro, cardiothoracic, and breast imaging subspecialties, the number of investigated and real-world applications of body imaging has been increasing, with more than 30 FDA-approved algorithms now available for applications in the abdomen and pelvis. In this manuscript, we explore some of the fundamentals of artificial intelligence and machine learning, review major functions that AI algorithms may perform, introduce current and potential future applications of AI in abdominal imaging, provide a basic understanding of the pathways by which AI algorithms can receive FDA approval, and explore some of the challenges with the implementation of AI in clinical practice.

Yuyang Jiang, Chacha Chen, Dang Nguyen, Benjamin M. Mervak, Chenhao Tan. Findings of the Association for Computational Linguistics: NAACL 2025. 2025.