Prediction of benign and malignant pulmonary nodules using preoperative CT features: using PNI-GARS as a predictor.

Journal: Frontiers in immunology

PMID: 39635520

Abstract

PURPOSE: The aim of this study was to develop and validate a prediction model for classification of pulmonary nodules based on preoperative CT imaging.

Authors

Yuxin Zhan

School of Science, Chongqing University of Technology, Chongqing, China.
Feipeng Song

Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Wenjia Zhang
Tong Gong

Institute of Drug R&D, Nanjing University, Nanjing 210093, China.
Shuai Zhao

Xi'an Medical University, Xi'an Shaanxi, 710068, P.R.China.
Fajin Lv

Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Keywords

Adult Aged Female Humans Lung Neoplasms Machine Learning Male Middle Aged Multiple Pulmonary Nodules Retrospective Studies Solitary Pulmonary Nodule Tomography, X-Ray Computed

External Resources

View on PubMed Access via DOI PubMed (39635520)

Prediction of benign and malignant pulmonary nodules using preoperative CT features: using PNI-GARS as a predictor.

Abstract

Authors

Keywords

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