Abstract

Early detection of pancreatic cancer is difficult, and thus many cases of pancreatic cancer are diagnosed late. When pancreatic cancer is detected, the cancer is usually well developed. Machine learning is an approach that is part of artificial intelligence and can detect pancreatic cancer early. This paper proposes a machine learning approach with the twin support vector machine (TWSVM) method as a new approach to detecting pancreatic cancer early. TWSVM aims to find two symmetry planes such that each plane has a distance close to one data class and as far as possible from another data class. TWSVM is fast in building a model and has good generalizations. However, TWSVM requires kernel functions to operate in the feature space. The kernel functions commonly used are the linear kernel, polynomial kernel, and radial basis function (RBF) kernel. This paper uses the TWSVM method with these kernels and compares the best kernel for use by TWSVM to detect pancreatic cancer early. In this paper, the TWSVM model with each kernel is evaluated using a 10-fold cross validation. The results obtained are that TWSVM based on the kernel is able to detect pancreatic cancer with good performance. However, the best kernel obtained is the RBF kernel, which produces an accuracy of 98%, a sensitivity of 97%, a specificity of 100%, and a running time of around 1.3408 s.

Highlights

  • According to the World Health Organization (WHO), the second leading cause of death in the world is cancer [1]

  • The best kernel obtained is the radial basis function (RBF) kernel, which produces an accuracy of 98%, a sensitivity of 97%, a specificity of 100%, and a running time of around 1.3408 s

  • This paper proposes the twin support vector machine (TWSVM) method as a novel approach for early detection of pancreatic cancer

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Summary

Introduction

According to the World Health Organization (WHO), the second leading cause of death in the world is cancer [1]. Pancreatic cancer is the seventh leading cause of cancer deaths in the world and ranks as the 14th most common cancer [3]. Based on the Global Cancer Observatory in 2018, the estimated number of diagnoses of this cancer in the world is 458,918 and the estimated number of deaths is 432,242 [4]. This cancer is expected to be the second leading cause of cancer deaths in the world in 2030 [5]

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