Identification of pathological subtypes of early lung adenocarcinoma based on artificial intelligence parameters and CT signs
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DOI: 10.1042/bsr20212416
Abstract: Abstract Objective: To explore the value of quantitative parameters of artificial intelligence (AI) and computed tomography (CT) signs in identifying pathological subtypes of lung adenocarcinoma appearing as ground-glass nodules (GGNs). Methods: CT images of 224… read more here.
Keywords: artificial intelligence; lung adenocarcinoma; early lung; pathological subtypes ... See more keywords