Coreline Soft Expands Lung Cancer Screening AI Beyond Detection to Integrated Screening and Follow-Up Management
Artificial intelligence in lung cancer screening is moving beyond the early detection of pulmonary nodules toward integrated screening operations, longitudinal imaging analysis and patient follow-up management.While the initial focus of AI development centered on identifying smaller lung cancers earlier through low-dose computed tomography (LDCT), attention is increasingly shifting to how…
As lung cancer screening AI evolves, the focus is shifting from merely detecting pulmonary nodules to integrating screening operations, analyzing data over time and managing patient follow-up. This transition is a key theme at the 50th International Conference on Screening for Lung Cancer, taking place in New York from October 22-24, 2026.
Organized by the International Early Lung Cancer Action Program (I-ELCAP), the conference is also hosting the 18th Conference on Early Lung Cancer Research on Treatment. With I-ELCAP originating in 1992 as a two-institution research network, it has grown into an international collaborative involving around 80 institutions. Since 1999, I-ELCAP conferences have discussed LDCT screening protocols, early detection, repeat examinations and long-term patient follow-up.
Beyond nodule detection, the conference program includes presentations on cardiovascular screening and Lung-RADS, a standardized system for reporting and managing lung cancer screening. LDCT scans often reveal additional health risks such as emphysema or coronary artery calcification, prompting interest in opportunistic imaging analysis to extract more diagnostic information.
As screening programs expand, the need for robust medical imaging AI becomes more pressing. Radiologists must compare current scans with previous ones to assess changes in nodule characteristics. Large-scale programs require standardized reporting, consistent follow-up recommendations and reliable patient tracking systems, especially when exams and interpretations occur across different institutions.
I-ELCAP has long viewed lung cancer screening as an ongoing clinical process, not a one-time diagnostic event. Participating centers collect and manage screening images and clinical data while tracking follow-up exams and treatment outcomes over time. The success of AI-assisted screening depends not only on algorithm accuracy but also on effectively incorporating findings into patient care.
Coreline Soft, a South Korean medical imaging AI company, is participating in the conference's Technology Innovation Session. Lead Jang Ryeong-woo will present a hub-based screening platform called "One Platform, Every Patient." Coreline Soft's AVIEW LCS software supports pulmonary nodule detection, comparison with prior CTs, quantitative measurements and structured reporting.
AVIEW HUB aims to connect imaging and interpretation information across institutions, streamlining screening workflows in national and multi-center environments. The company's goal is to provide healthcare providers with integrated tools for managing imaging data, standardizing interpretation processes and supporting repeated screening exams.
Written by urgent.news from Korea IT Times's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
