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This article discusses the use of a multi-omic analytic platform to accurately predict disease status after surgery in patients with resectable pancreatic cancer. The platform incorporates advanced molecular profiling and machine learning models to identify biomarkers that can predict disease status. The study found that plasma protein is the most critical biomarker for survival and is superior to the commonly used CA 19-9 marker. This approach has the potential to impact clinical care and scientific discovery for all types of cancer.
