Objective: Accurate, easily accessible and economically viable cancer diagnostic tools are pivotal in improving the abysmal 5% survival rate of pancreatic cancer.
Methods: A novel, affordable, non-invasive diagnostic method has been developed by combining measurement precision of infrared spectroscopy with classification using machine learning tools.
Results: Diagnosis accuracy as high as 90% has been achieved. The study investigated urine and blood from pancreas cancer patients and healthy volunteers, and significantly improved accuracy by focusing on sweet-spots within blood plasma fractions containing molecules within a narrow range of molecular weights.
Keywords: FTIR; PCA; SVM; biomarker; cancer; diagnosis; pancreatic; spectroscopy.
© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.