First published 10/3/2026, 12:37:15 AM · Last updated 10/3/2026, 12:37:15 AM

P1.04.39 Markov Model Approach to Optimize Lung Cancer Screening and Early Detection in Patients With Smoking Associated Diseases

A journal article reports a Markov-model-based approach to optimize lung cancer screening and early detection for patients with smoking-associated diseases. Publisher is Elsevier BV and the article was published 2025-10-01.

Illustrative image: A549 cells are isolated from the lung tissue of a 58-year-old Caucasian male with lung cancer. Use this cell line for your cancer, immuno-oncology, and toxicology research and high-throughput screening. — Pinyapat Prisananuntakul/Wikimedia Commons, CC BY 4.0

Categories: public-health

Generated scores

Scores are based on the cited reporting and use a 1–10 scale. Read the methodology.

Confidence: 5/10How certain the assessment is based on the clarity and evidence in the cited reporting.
Geographic reach: 1/10How widely the event reaches, from a local area (1) to worldwide impact (10).
Global importance: 3/10The event's broader significance, from limited importance (1) to major global importance (10).
Impact magnitude: 3/10The scale or severity of the real-world impact, from minor (1) to extreme (10).
Positivity: 7/10How harmful or beneficial the event is, from strongly harmful (1) to strongly positive (10).
Urgency: 2/10How time-sensitive the event is, from low urgency (1) to immediate attention needed (10).

Why it matters

Optimizing screening and early detection targets improving identification of lung cancer in people with smoking-associated diseases.

Sources

P1.04.39 Markov Model Approach to Optimize Lung Cancer Screening and Early Detection in Patients With Smoking Associated Diseases

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