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Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches.

Matthew T WarkentinHamad Al-SawaiheyStephen LamGeoffrey LiuBrenda DiergaardeJian-Min YuanDavid O WilsonSukhinder Atkar-KhattraBenjamin GrantYonathan BrhaneElham Khodayari-MoezKiera R MurisonMartin C TammemagiKieran R CampbellRayjean J Hung
Published in: Thorax (2024)
We developed highly accurate ML models based on radiomic and epidemiological features from four international lung cancer screening studies that may be suitable for assessing indeterminate screen-detected pulmonary nodules for risk of malignancy.
Keyphrases
  • pulmonary hypertension
  • high resolution
  • magnetic resonance imaging
  • squamous cell carcinoma
  • computed tomography
  • magnetic resonance
  • fine needle aspiration
  • ultrasound guided