Optimization of Classification Model for Early Detection of Pancreatic Cancer Using GridSearchCV and Autoencoder

Stefanie Quinevera, Ahmad Saikhu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Pancreatic Ductal Adenocarcinoma (PDAC) is one of the most difficult cancers to detect, often diagnosed at advanced stages. PDAC is the seventh most common cause of death worldwide. Due to malignant tumors with an extremely poor prognosis, more than 75% of patients are discovered at an advanced stage, and only 7% of patients survive for five years following diagnosis. Early detection of PDAC is crucial for improving patient survival rates. This study develops a machine learning model for the early detection of PDAC using Gradient Boosting Classifier (GBC) and Light Gradient Boosting Machine (LightGBM) algorithms with GridSearchCV optimization and Autoencoder methods to handle missing values. The dataset used is Urinary Biomarkers for Pancreatic Cancer from Kaggle. The results show that the LightGBM model, optimized with GridSearchCV, surpasses the GBC model in distinguishing patient types. The LightGBM model achieved an accuracy of 77.45% before optimization and improved to 78.81% after GridSearchCV optimization. This emphasizes the effectiveness of GridSearchCV in optimizing hyperparameters to improve classification performance.

Original languageEnglish
Title of host publication2024 8th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-137
Number of pages5
ISBN (Electronic)9798350368970
DOIs
Publication statusPublished - 2024
Event8th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2024 - Hybrid, Yogyakarta, Indonesia
Duration: 29 Aug 202430 Aug 2024

Publication series

Name2024 8th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2024

Conference

Conference8th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2024
Country/TerritoryIndonesia
CityHybrid, Yogyakarta
Period29/08/2430/08/24

Keywords

  • Autoencoder
  • GBC
  • GridSearchCV
  • LightGBM
  • PDAC

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