A pancreatic cancer detection support tool using mass spectrometry data and support vector machines

• Main Authors: Briones, Emmanuel, Lao, Angelyn R., Solano, Geoffrey A.
• Format: text
• Published: Animo Repository 2020
• Subjects: Biochemical markers; Pancreas—Cancer—Diagnosis; Mass spectrometry; Machine learning; Support vector machines; Medicine and Health Sciences; Physical Sciences and Mathematics
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2292; https://animorepository.dlsu.edu.ph/context/faculty_research/article/3291/type/native/viewcontent
• Institution: De La Salle University

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.