Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy.
Yangyang ZhuZheling MengXiao FanYin DuanYingying JiaTiantian DongYanfang WangJuan SongJie TianKun WangFang NiePublished in: BMC medicine (2022)
Multi-cohort testing demonstrated our DL model integrating dual-modality ultrasound images achieved accurate diagnosis of unexplained CLA. With its assistance, the gap between radiologists with different levels of experience was narrowed, which is potentially of great significance for benefiting CLA patients in underdeveloped countries and regions worldwide.
Keyphrases
- deep learning
- convolutional neural network
- artificial intelligence
- magnetic resonance imaging
- end stage renal disease
- ejection fraction
- newly diagnosed
- optical coherence tomography
- prognostic factors
- peritoneal dialysis
- machine learning
- patient reported outcomes
- high resolution
- computed tomography
- lymph node metastasis
- magnetic resonance
- contrast enhanced
- patient reported