Paper Key : IRJ************979
Author: J.jacob Daniel
Date Published: 09 Apr 2024
Abstract
Pancreatic cancer is the fourth most common cancer-related cause of death in the United States and is usually asymptomatic in early stages. There is a scarcity of tests that facilitate early diagnosis or accurately predict the disease progression. To this end, biomarkers have been identified as important tools in the diagnosis and management of pancreatic cancer. Despite the increasing number of biomarkers described in the literature, most of them have demonstrated moderate sensitivity and specificity and are far from being considered as screening tests. More efficient non-invasive biomarkers are needed to facilitate early-stage diagnosis and interventions. Multi-disciplinary collaboration might be required to facilitate the identification of such markers. Data mining is a commonly used technique for processing enormous data. Researchers apply several data mining and machine learning techniques to analyse huge complex data, to helping the prediction of pancreatic cancer. Different algorithms are compared and the best model is used for predicting the outcome
DOI LINK : 10.56726/IRJMETS51943 https://www.doi.org/10.56726/IRJMETS51943