Real world evidence is crucial to understanding the diffusion of new oncologic therapies, monitoring cancer outcomes, and detecting unexpected toxicities. In practice, real world evidence is challenging to collect rapidly… Click to show full abstract
Real world evidence is crucial to understanding the diffusion of new oncologic therapies, monitoring cancer outcomes, and detecting unexpected toxicities. In practice, real world evidence is challenging to collect rapidly and comprehensively, often requiring expensive and time‐consuming manual case‐finding and annotation of clinical text. In this Review, we summarise recent developments in the use of artificial intelligence to collect and analyze real world evidence in oncology.
Keywords:
oncology;
real world;
artificial intelligence;
world evidence
Journal Title: Cancer Medicine
Year Published: 2024
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Journal Title: Cancer Medicine
Year Published: 2024
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!