Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor.
Wataru ShigeedaRyuichi YosihimuraYuji FujitaHidekazu SaikiHiroyuki DeguchiMakoto TomoyasuSatoshi KudoYuka KanekoHironaga KannoYoshihiro InoueHajime SaitoPublished in: Thoracic cancer (2021)
MS combined with an AI system demonstrated high accuracy not only for differentiating cancer from normal tissue, but also for differentiating between PLAC and CRMPT with a short working time. This method shows potential for application as a support tool facilitating rapid intraoperative diagnosis to determine the surgical procedure for pulmonary resection.
Keyphrases
- artificial intelligence
- mass spectrometry
- machine learning
- big data
- pulmonary hypertension
- contrast enhanced
- deep learning
- liquid chromatography
- papillary thyroid
- small cell lung cancer
- squamous cell carcinoma
- multiple sclerosis
- ms ms
- magnetic resonance imaging
- high performance liquid chromatography
- gas chromatography
- computed tomography
- minimally invasive
- risk assessment
- young adults
- lymph node metastasis
- loop mediated isothermal amplification
- climate change
- simultaneous determination