Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules.

ABSTRACT:

Background

Pulmonary Nodules (PNs) are a trend considered as the early manifestation of lung cancer. Among them, PNs that remain stable for more than two years or whose pathological results suggest not being lung cancer are considered benign PNs (BPNs), while PNs that conform to the growth pattern of tumors or whose pathological results indicate lung cancer are considered malignant PNs (MPNs). Currently, more than 90% of PNs detected by screening tests are benign, with a false positive rate of up to 96.4%. While a range of predictive models have been developed for the identification of MPNs, there are still some challenges in distinguishing between BPNs and MPNs.

Methods

We included a total of 5197 patients for the case-control study according to the preset exclusion criteri

SUBMITTER: Li Z 

PROVIDER: S-EPMC12275455 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature