AI-Decision Support System Interface Using Cancer Related Data for Lung Cancer Prognosis

TL;DR

This paper presents a web-based decision support system that leverages machine learning algorithms to predict lung cancer prognosis using clinical and gene expression data, aiding early diagnosis and treatment planning.

Contribution

It introduces a novel web interface integrating machine learning models for lung cancer prognosis based on clinical and gene expression data.

Findings

Effective prediction of lung cancer prognosis using the system.

Integration of clinical and gene expression data improves accuracy.

Provides a user-friendly tool for clinicians and researchers.

Abstract

Until the beginning of 2021, lung cancer is known to be the most common cancer in the world. The disease is common due to factors such as occupational exposure, smoking and environmental pollution. The early diagnosis and treatment of the disease is of great importance as well as the prevention of the causes that cause the disease. The study was planned to create a web interface that works with machine learning algorithms to predict prognosis using lung cancer clinical and gene expression in the GDC data portal.