Machine learning-based radiomics to distinguish pulmonary nodules between lung adenocarcinoma and tuberculosis.
Yuan LiBaihan LyuRong WangYue PengHaoyu RanBolun ZhouYang LiuGuangyu BaiQilin HuaiXiaowei ChenChun ZengQingchen WuCheng ZhangShugeng GaoPublished in: Thoracic cancer (2024)
The present study established a machine learning-based radiomics strategy for differentiating LUAD from TB lesions. The ROI segmentation including or excluding the cavity region may exert no significant effect on the predictive ability.
Keyphrases
- machine learning
- mycobacterium tuberculosis
- deep learning
- contrast enhanced
- lymph node metastasis
- artificial intelligence
- big data
- pulmonary hypertension
- convolutional neural network
- magnetic resonance imaging
- pulmonary tuberculosis
- squamous cell carcinoma
- emergency department
- hiv aids
- computed tomography
- hiv infected
- drug induced
- antiretroviral therapy
- human immunodeficiency virus
- electronic health record