Generative artificial intelligence: In the search for new landscapes in basic and clinical nephrology

Abstract

The rise of systems biology has improved the understanding of complex disorders such as chronic kidney disease by providing predictive and comprehensive models. Despite the abundance of omics data, translation to clinical solutions remains a challenge. Artificial intelligence (AI), especially generative AI, promises to fill this gap through mining, integration, and processing of diverse and intricate raw data for the generation of actionable knowledge. Recently introduced AI tools have shown great potential in clinical nephrology for improved diagnosis and prognosis. This approach is also promising for the identification of novel therapeutic targets, repurposing of already approved drugs, and precision nephrology. The rapid advancement of this technology is definitely associated with critical ethical and legal concerns for which the scientific community needs to be prepared.