Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models
Zhengsong Pan, Ge Hu, Zhenchen Zhu, Weixiong Tan, Wei Han, Z.‐G. Zhou, Wei Song, Yizhou Yu, Lan Song, Zhengyu Jin
Abstract
Performance of deep learning models for predicting preinvasive, minimally invasive, or invasive adenocarcinoma was improved by combining binary and ternary classification models for predicting invasiveness and adjudication of discordant classification.
Topics & Concepts
MedicineAdenocarcinomaRadiologyBinary classificationArtificial intelligenceSolitary pulmonary noduleLung cancer screeningTest setCancerComputed tomographyInternal medicineComputer scienceSupport vector machineLung Cancer Diagnosis and TreatmentRadiomics and Machine Learning in Medical ImagingMedical Imaging Techniques and Applications