Employment of artificial intelligence for early lung cancer diagnosis: a retrospective cohort study.

Nathan R Hill¹, Travis Dotson², Sarah E Maus², Christina Bellinger², Vishisht Mehta³, Annika Rings⁴, Lyndsey C Pickup⁵, Noah Waterfield Price⁵, Václav Potěšil⁵, David P Carbone⁶, Jasleen Pannu⁷

¹Bristol-Myers Squibb Co R&D Lawrenceville, Lawrenceville, New Jersey, USA.

²Pulmonary/Critical Care, Atrium Health Wake Forest Baptist, Winston-Salem, North Carolina, USA.

³Comprehensive Cancer Centers of Nevada, Henderson, Nevada, USA.

⁴Optellum Ltd, Oxford, UK annika.rings@optellum.com.

⁵Optellum Ltd, Oxford, UK.

⁶The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, USA.

⁷The Ohio State University Wexner Medical Center, Columbus, Ohio, USA.

PubMed PMC DOI PDF

Abstract

AIM: This study aims to evaluate the effectiveness of combined artificial intelligence (AI)-based tools for early patient identification, risk stratification and tracking in increasing the follow-up rate of incidentally detected lung nodules, potentially leading to earlier diagnoses of lung cancer, particularly non-small cell lung cancer (NSCLC). PATIENTS AND METHODS: We conducted a retrospective…

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