A Fusion-based Radiomics Approach Combining Tumor, Peritumoral, and Habitat Features for Predicting Visceral Pleural Invasion in Stage IA Lung Adenocarcinoma

This publication has 25 references indexed in Scilit:

• Comparing Habitat, Radiomics, and Fusion Models for Predicting Micropapillary/Solid Components in Stage I Lung Adenocarcinoma
  Academic Radiology, 2025
• Nomogram based on radiomics and CT features for predicting visceral pleural invasion of invasive adenocarcinoma ≤ 2 cm: A multicenter study
  European Journal of Radiology, 2025
• Peritumoral and intratumoral radiomics for predicting visceral pleural invasion in lung adenocarcinoma based on preoperative computed tomography (CT)
  Clinical Radiology, 2024
• Computed Tomography-derived intratumoral and peritumoral radiomics in predicting EGFR mutation in lung adenocarcinoma
  La radiologia medica, 2023
• One-off low-dose CT for lung cancer screening in China: a multicentre, population-based, prospective cohort study
  The Lancet Respiratory Medicine, 2022
• Lung cancer
  The Lancet, 2021
• Selecting the most important self-assessed features for predicting conversion to mild cognitive impairment with random forest and permutation-based methods
  Scientific Reports, 2020
• Sub-region based radiomics analysis for survival prediction in oesophageal tumours treated by definitive concurrent chemoradiotherapy
  EBioMedicine, 2019
• The IASLC Lung Cancer Staging Project: Methodology and Validation Used in the Development of Proposals for Revision of the Stage Classification of NSCLC in the Forthcoming (Eighth) Edition of the TNM Classification of Lung Cancer
  Journal of Thoracic Oncology, 2016
• The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer
  Journal of Thoracic Oncology, 2016