首页|Nanjing Medical University Affiliated Cancer Hospital Reports Findings in Solita ry Pulmonary Nodule (Dual-layer detector spectral CT-based machine learning mode ls in the differential diagnosis of solitary pulmonary nodules)
Nanjing Medical University Affiliated Cancer Hospital Reports Findings in Solita ry Pulmonary Nodule (Dual-layer detector spectral CT-based machine learning mode ls in the differential diagnosis of solitary pulmonary nodules)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Lung Diseases and Cond itions-Solitary Pulmonary Nodule is the subject of a report. According to news originating from Nanjing, People's Republic of China, by NewsRx correspondents, research stated, "The benign and malignant status of solitary pulmonary nodules (SPNs) is a key determinant of treatment decisions." Our news journalists obtained a quote from the research from Nanjing Medical Uni versity Affiliated Cancer Hospital, "The main objective of this study was to val idate the efficacy of machine learning (ML) models featured with dual-layer dete ctor spectral computed tomography (DLCT) parameters in identifying the benign an d malignant status of SPNs. 250 patients with pathologically confirmed SPN were included in this study. 8 quantitative and 16 derived parameters were obtained b ased on the regions of interest of the lesions on the patients' DLCT chest enhan cement images. 6 ML models were constructed from 10 parameters selected after co mbining the patients' clinical parameters, including gender, age, and smoking hi story. The logistic regression model showed the best diagnostic performance with an area under the receiver operating characteristic curve (AUC) of 0.812, accur acy of 0.813, sensitivity of 0.750 and specificity of 0.791 on the test set." According to the news editors, the research concluded: "The results suggest that the ML models based on DLCT parameters are superior to the traditional CT param eter models in identifying the benign and malignant nature of SPNs, and have gre ater potential for application."
NanjingPeople's Republic of ChinaAsi aCyborgsDiagnostics and ScreeningEmerging TechnologiesHealth and Medicin eLung Diseases and ConditionsLung NeoplasmsMachine LearningRespiratory T ract Diseases and ConditionsRespiratory Tract NeoplasmsSolitary Pulmonary No dule
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