Article ; Online: Frontline clinical diagnosis-FTIR on pancreatic cancer.
2023 Volume 12, Issue 16, Page(s) 17340–17345
Abstract: 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 ... ...
Abstract | 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. |
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MeSH term(s) | Humans ; Spectroscopy, Fourier Transform Infrared/methods ; Pancreatic Neoplasms/diagnosis ; Machine Learning ; Pancreatic Neoplasms |
Language | English |
Publishing date | 2023-07-19 |
Publishing country | United States |
Document type | Journal Article ; Research Support, Non-U.S. Gov't |
ZDB-ID | 2659751-2 |
ISSN | 2045-7634 ; 2045-7634 |
ISSN (online) | 2045-7634 |
ISSN | 2045-7634 |
DOI | 10.1002/cam4.6346 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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