Work

Detection of Lung Nodules from CT Image Based on Ensemble Learning

Year: 2025

Type: conference-paper

Abstract: Lung cancer is the most frequently diagnosed cancer worldwide and the leading cause of cancer-related deaths, making early detection and treatment crucial.Temporal subtraction system, one of the CAD, emphasize the differences between the current and previous images.In this study, radiomics features are extracted as explanatory variables from the temporal subtraction images.Feature selection is performed using Elastic Net, followed by the application of machine learning methods.Finally, ensemble learning is applied to classify unknown data into two categories: positive and negative lung nodules.

Source: Proceedings of International Conference on Artificial Life and Robotics

DOI: 10.5954/icarob.2025.gs2-4

Authors: Natsuho Baba, Tohru Kamiya, Takashi Terasawa, Takatoshi Aoki

Institutions: Kyushu Institute of Technology, University of Occupational and Environmental Health Japan

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

OpenAlex ID: W4409913872