Researchers are working on developing artificial intelligence frameworks to improve the diagnosis of non-small cell lung cancer, with a focus on making the technology more trustworthy and interpretable. Various approaches are being explored, including the use of deep learning and hybrid architectures, as well as the integration of clinical insights and claims data. The goal of these efforts is to enhance the accuracy and reliability of lung cancer diagnoses, although the specifics of the different approaches and their potential outcomes are not yet clear.