Leveraging Deep Learning Decision-Support System in Specialized Oncology Center

KVAK, Daniel, Anna CHROMCOVÁ, Robert HRUBÝ, Eva JANŮ, Marek BIROŠ, Marija PAJDAKOVIĆ, Karolína KVAKOVÁ, Pavlína POLÁŠKOVÁ and Sergei STRUKOV. Leveraging Deep Learning Decision-Support System in Specialized Oncology Center. In European Congress of Radiology 2023, Vienna. 2023.

Basic information

• Original name: Leveraging Deep Learning Decision-Support System in Specialized Oncology Center
• Authors: KVAK, Daniel, Anna CHROMCOVÁ, Robert HRUBÝ, Eva JANŮ, Marek BIROŠ, Marija PAJDAKOVIĆ, Karolína KVAKOVÁ, Pavlína POLÁŠKOVÁ and Sergei STRUKOV.
• Edition: European Congress of Radiology 2023, Vienna, 2023.

Other information

• Original language: English
• Type of outcome: Conference abstract
• Country of publisher: Austria
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• Tags: International impact, Reviewed

Abstract

Chest X-ray (CXR) is one of the most common diagnostic imaging tests to identify and monitor various chest findings, including pulmonary lesions that may be indicative of, among other pathologies, lung cancer. However, the effectiveness of X-ray imaging in detecting both primary and secondary tumors is not always reliable. The aim of our study was to demonstrate the effectiveness of the proposed deep learning-based algorithm (DLAD) for detecting pulmonary lesions on CXR images and to compare its performance with that of radiologists with different levels of experience in a simulated clinical setting. The proposed DLAD demonstrated improved detection performance compared to existing conventional imaging-based diagnostics, as it showed a significantly lower false-negative rate while also providing relatively high specificity.