As rapid population aging and healthcare workforce shortages intensify, medical artificial intelligence (AI) is evolving from a pilot technology to an operational infrastructure supporting hospital management. The World Health Organization (WHO) projects a global shortage of 11 million healthcare workers by 2030. In South Korea, where the elderly population now exceeds 20 percent, rising imaging demand and limited specialist resources have emerged as structural challenges.
Against this backdrop, the Department of Radiology at Wonkwang University Hospital has introduced an AI-integrated diagnostic workflow based on chest CT imaging. The model applies Coreline Soft’s AVIEW LCS solution across all chest CT scans to detect small pulmonary nodules, establishing a systematic safety net for radiologic interpretation.
Unlike limited pilot programs targeting specific patient groups, the system embeds AI into the hospital’s standard imaging protocol, reflecting a comprehensive operational approach.
North Jeolla Province, where the hospital is located, has an elderly population exceeding 25 percent, with a high proportion of patients at risk for overlapping respiratory and cardiovascular diseases. To address these regional characteristics, the hospital implemented an AI-assisted reading safety net to minimize missed lesions.
Se Ri Kang MD, Assistant Professor, Department of Radiology, Department of Medicine, Wonkwang University School of Medicine & Hospital, said integrating AI as a core component of the reading environment improves diagnostic consistency and enhances clarity in patient communication.
Operational efficiency has also improved. By introducing AI-driven automated analysis in cardiac CT workflows, the hospital reduced repetitive tasks and alleviated bottlenecks in examination processes. The hospital evaluates the impact not merely as time savings but as a structural enhancement of imaging capacity. The results were presented at the Korean Congress of Radiology (KCR), with further academic validation underway.
Coreline Soft noted that the case demonstrates a shift in how medical AI is assessed — from pure accuracy metrics to measurable operational contribution. When AI functions as infrastructure supporting risk management, workforce optimization and standardized patient communication, it can strengthen the sustainability of hospital operations.
The company plans to expand its integrated multi-disease chest CT analysis model and gradually introduce standardized AI-enabled workflows to regional hub hospitals.
