A pancreatic cancer detection support tool using mass spectrometry data and support vector machines
College
College of Science
Department/Unit
Mathematics and Statistics Department
Document Type
Conference Proceeding
Source Title
2020 International Conference on Artificial Intelligence and Signal Processing, AISP 2020
Publication Date
1-1-2020
Abstract
Pancreatic cancer is one of the most fatal types of cancer due to its difficulty of being diagnosed in the early stages. Presently, multiple screening procedures for this disease are required to determine its presence. In this study, a pancreatic detection support tool implementing machine learning is to be created with support vector machines (SVM) algorithm and mass spectrometry data of pancreatic cancer patients and controls as training and testing datasets. The final output would aid researchers in detecting pancreatic cancer in patients (complementing current and common procedures), and in finding biomarkers of the disease. © 2020 IEEE.
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Digitial Object Identifier (DOI)
10.1109/AISP48273.2020.9073503
Recommended Citation
Briones, E., Lao, A. R., & Solano, G. A. (2020). A pancreatic cancer detection support tool using mass spectrometry data and support vector machines. 2020 International Conference on Artificial Intelligence and Signal Processing, AISP 2020 https://doi.org/10.1109/AISP48273.2020.9073503
Disciplines
Medicine and Health Sciences | Physical Sciences and Mathematics
Keywords
Biochemical markers; Pancreas—Cancer—Diagnosis; Mass spectrometry; Machine learning; Support vector machines
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