Predicting the Recurrence of Gastric Cancer using Machine Learning
Journal Title: International Journal for Modern Trends in Science and Technology - Year 2024, Vol 10, Issue 9
Abstract
Gastric cancer, also known as stomach cancer, is a type of cancer that originates in the cells lining the stomach. The stomach is a vital organ in the digestive system, responsible for breaking down food and aiding in the digestion process. Gastric cancer remains a significant global health concern, with early detection being crucial for improving patient outcomes. Machine learning (ML) techniques have emerged as promising tools for predicting gastric cancer risk, enabling early diagnosis and intervention. This abstract provides an overview of ML-based approaches for gastric cancer prediction, highlighting their potential impact on healthcare delivery and patient outcomes. Traditional methods for gastric cancer risk assessment often rely on clinical factors such as age, gender, and family history, but may lack the sensitivity and specificity required for effective screening. Supervised learning algorithms, including support vector machine and Random Forest is used for testing accuracy are commonly employed to analyse these multidimensional datasets and identify patterns indicative of gastric cancer risk
Authors and Affiliations
R. Siva, K. Siva, M. Harshavardhini, K V D S Akhil, K Sai Aditya
Keywords
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- EP ID EP747884
- DOI https://doi.org/10.46501/IJMTST1009005
- Views 56
- Downloads 1
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