Predicting Invasiveness in Lung Adenocarcinoma with Ground-Glass Nodules Through Machine Learning and Radiomic Analysis of Clinical CT Data - Quiz - MDSpire

Predicting Invasiveness in Lung Adenocarcinoma with Ground-Glass Nodules Through Machine Learning and Radiomic Analysis of Clinical CT Data

  • By

  • Mingzhi Lin

  • Longqian Li

  • Yiming Hui

  • Bin Li

  • Yue Li

  • ChongRui Li

  • Zhizhong Zheng

  • Zhuowen Yang

  • November 3, 2025

  • 0 min

Share

Original Source(s)

Predicting Invasiveness in Lung Adenocarcinoma with Ground-Glass Nodules Through Machine Learning and Radiomic Analysis of Clinical CT Data

  • by Mingzhi Lin, Longqian Li, Yiming Hui, Bin Li, Yue Li, ChongRui Li, Zhizhong Zheng, Zhuowen Yang

  • November 3, 2025

Related Content

Endocrine therapy and thyroid function in early luminal breast cancer: a controlled longitudinal retrospective analysis

Homologous recombination pathway alterations in basal-like breast cancer

Case Report: Safety and efficacy of blinatumomab in combination with donor lymphocyte infusion for the prophylaxis of relapse following allogeneic hematopoietic stem cell transplantation in a pediatric patient with acute lymphoblastic leukemia