Diagnosis of Metastatic Lymph Nodes in Patients with Papillary Thyroid Cancer: A Comparative Multi-Center Study of Semantic Features and Deep Learning-Based Models.
Ali Abbasian ArdakaniAfshin MohammadiMohammad Mirza-Aghazadeh-AttariFariborz FaeghiThomas J VoglU Rajendra AcharyaPublished in: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine (2022)
A deep learning model trained with ultrasound images outperformed three conventional machine learning algorithms fed with qualitative imaging features interpreted by radiologists. Our study provides evidence regarding the utility of ClymphNet in the early and accurate differentiation of benign and malignant lymphadenopathy.
Keyphrases
- deep learning
- papillary thyroid
- machine learning
- artificial intelligence
- lymph node
- convolutional neural network
- lymph node metastasis
- high resolution
- squamous cell carcinoma
- small cell lung cancer
- magnetic resonance imaging
- systematic review
- big data
- young adults
- optical coherence tomography
- body composition
- resistance training
- ultrasound guided