Table 1_Machine learning-based differentiation of lung squamous cell carcinoma and adenocarcinoma using clinical-semantic and radiomic features.docx

Table 1_Machine learning-based differentiation of lung squamous cell carcinoma and adenocarcinoma using clinical-semantic and radiomic features.docx

Purpose<p>To evaluate and compare the predictive performance of machine learning methods using clinical-semantic, radiomic, and combined features in distinguishing squamous cell carcinoma (SCC) from adenocarcinoma (ADC) in non-small cell lung cancer (NSCLC).</p>Methods<p>A total of...

Descrición completa

Gardado en:
Detalles Bibliográficos
Autor Principal: Yanju Li (9697993) (author)
Outros autores: Xiaomeng Yang (702951) (author), Yingjin Zhang (20532682) (author), Jing Liang (32441) (author), Jiaxin Liu (833821) (author), Xinru Zheng (16801562) (author), Jing Wang (6206297) (author), Zhaoxiang Ye (4468483) (author)
Publicado: 2025
Subjects:
Oncology and Carcinogenesis not elsewhere classified
squamous cell carcinoma
adenocarcinoma
radiomics
machine learning
computed tomography
Tags: Engadir etiqueta
Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!

Títulos similares

Títulos similares