An ensemble learning with active sampling to predict the prognosis of postoperative non-small cell lung cancer patients

HIGHLIGHTS

• who: Danqing Hu from the We reviewed , NSCLC patients who had undergone curative surgery from , to , in the Department of Thoracic Surgery II of Peking University Cancer HospitalThe collected data covered patient demographic information, preoperative exams and treatments, pathological information of the primary tumor and lymph nodes, and the pathological TNM stage. Clinicians manually recorded all the clinical data to ensure its reliability and correctness. The details of the clinical data are listed in the Additional file, . Before model development, we preprocessed the collected clinical data. Specifically, patient samples with missing feature values were excluded from the . . .
  

   

  

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