The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations.

Journal: BMC cancer
PMID: 40001094

Abstract

BACKGROUND: Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibility and cost-effectiveness analysis of a community-based program that used a mobile low-dose computed tomography (LDCT) scan unit and discuss the operational challenges faced during its implementation.

Authors

  • Feifei Huang
    School of Nursing, Fujian Medical University, Fuzhou, 350122, Fujian, China.
  • Xiujing Lin
  • Yuezhen Hong
    School of Nursing, Fujian Medical University, Fuzhou, 350122, Fujian, China.
  • Yue Li
    School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, China.
  • Yonglin Li
    School of Nursing, Fujian Medical University, Fuzhou, 350122, Fujian, China.
  • Wei-Ti Chen
    School of Nursing, University of California Los Angeles, Los Angeles, CA, USA.
  • Weisheng Chen

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