CNN-based Methods for Survival Prediction using CT images for Lung Cancer Patients

• Type: Article in International Conference Proceedings Book
• Date: 2024

Authors

Amaro, M (Author) Other; Oliveira, HP (Author) FCUP; Pereira, T (Author) Other

Conference proceedings International

Title: 2024 IEEE 37TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, CBMS 2024

Pages: 290-296

37th International Symposium on Computer-Based Medical Systems (CBMS)

Guadalajara, MEXICO, JUN 26-28, 2024

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Other information

Authenticus ID: P-016-DYW

DOI: 10.1109/cbms61543.2024.00055

Abstract (EN): Lung Cancer (LC) is still among the top main causes of death worldwide, and it is the leading death number among other cancers. Several AI-based methods have been developed for the early detection of LC, trying to use Computed Tomography (CT) images to identify the initial signs of the disease. The survival prediction could help the clinicians to adequate the treatment plan and all the proceedings, by the identification of the most severe cases that need more attention. In this study, several deep learning models were compared to predict the survival of LC patients using CT images. The best performing model, a CNN with 3 layers, achieved an AUC value of 0.80, a Precision value of 0.56 and a Recall of 0.64. The obtained results showed that CT images carry information that can be used to assess the survival of LC.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7