Artificial Intelligence‐Assisted Pulmonary Nodule Diagnosis by Thoracic Surgeons: A Comparative Study on Clinical Effectiveness
Yeong Jeong Jeon, Jonghun Jeong, Doohyun Park, Jung‐Hyun Kang, Eun Kyoung Hong, Younjoon Chung, Boram Park, Seong Yong Park · 2026
Read Artificial Intelligence‐Assisted Pulmonary Nodule Diagnosis by Thoracic Surgeons: A Comparative Study on Clinical Effectiveness by Yeong Jeong Jeon, Jonghun Jeong, Doohyun Park, Jung‐Hyun Kang, Eun Kyoung Hong, Younjoon Chung, Boram Park, Seong Yong Park (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13589327.txt.
Description
Yeong Jeong Jeon and seven co-authors test whether AI helps chest surgeons judge lung spots, in a study dated 2026. Small spots on lung scans may be harmless or may be cancer, and judgment varies with experience. The team asked if a computer-aided diagnosis system lifts accuracy for both junior and senior surgeons.
Twenty surgeons each read one hundred anonymized cases twice, once with the AI and once without, with a gap between rounds. The AI alone scored high on telling malignant from benign. With its help, all readers improved, and junior surgeons gained the most ground. Senior surgeons improved on a graded risk scale but not on the simple yes-or-no call. The study supports AI as a training-wheels tool that narrows the experience gap.
Catalog record
| CREATOR | Yeong Jeong Jeon, Jonghun Jeong, Doohyun Park, Jung‐Hyun Kang, Eun Kyoung Hong, Younjoon Chung, Boram Park, Seong Yong Park |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 39 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |