2024/10/13 by Negrini, Francesco, De Angelis, Luigi, Iosa, Marco +7
#Artificial Intelligence #Clinical Medicine #Medicine and Health Sciences #Other Medicine and Health Sciences
paper · doi:10.17605/osf.io/usb5j
In recent years, the integration of AI tools into various medical domains has become increasingly prevalent, yet it presents significant challenges in understanding and classification. Our study employs an “overview of systematic reviews” design, chosen specifically to provide a broad perspective on the use of AI in clinical medicine. By systematically reviewing the application of AI across different fields, we summarize findings from numerous systematic reviews (SRs) to illustrate the current landscape of AI use. A key component of our work is the introduction of the CLASMOD-AI framework, a novel approach aimed at enhancing the reporting of information in future reviews. This framework categorizes AI tools based on crucial aspects such as input, model, data training, performance metrics, and risk of bias, promoting greater consistency and transparency in reporting.