Machine Learning Based on Clinical Information and Integrated CT Radiomics to Predict Local Recurrence of Stage Ia Lung Adenocarcinoma after Microwave Ablation.

Journal: Journal of vascular and interventional radiology : JVIR
PMID: 39208929

Abstract

PURPOSE: To develop and compare 3 different machine learning-based models of clinical information and integrated radiomics features predicting the local recurrence of Stage Ia lung adenocarcinoma after microwave ablation (MWA) for assisting clinical decision making.

Authors

  • Shengmei Ma
    Department of Radiology, Qilu Hospital of Shandong University, Jinan, China.
  • Jingshuo Li
    Department of Radiology, Qilu Hospital of Shandong University, Jinan, China.
  • Yuxian Chen
    Department of Endocrinology, Institute of Translational Medicine, Health Science Center, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, Guangdong, China.
  • Ziqi Zhang
    Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA.
  • Li Hu
    CAS Key Laboratory of Mental Health, Institute of Psychology (CAS) Beijing, China.
  • Chunhai Li
    Department of Radiology, Qilu Hospital of Shandong University, Jinan, China.
  • Haipeng Jia
    Department of Radiology, Qilu Hospital of Shandong University, Jinan, China. Electronic address: yuejia17@163.com.

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