Machine learning to predict occult nodal metastasis in early oral squamous cell carcinoma

Keyphrases

• Algorithm Performance 16%
• Area under the Receiver Operating Characteristic Curve 16%
• Classification Performance 16%
• Clinical T1 33%
• Clinically Node-negative 16%
• Clinicopathologic Data 16%
• Decision Forest Algorithm 16%
• Depth of Invasion 66%
• Enhanced Sensitivity 16%
• Invasion Model 50%
• Machine Learning 100%
• Machine Learning Algorithms 16%
• Model Performance 16%
• Multiple Machines 16%
• National Cancer Database 33%
• Neck Dissection 50%
• Nodal Disease 16%
• Nodal Metastasis 33%
• Occult Nodal Disease 16%
• Occult Nodal Metastasis 100%
• Oral Tongue Squamous Cell Carcinoma (OTSCC) 100%
• Pathologic 50%
• Performance Prediction 16%
• Predictive Algorithm 16%
• Primary Tumor 16%
• Receiver Operating Characteristic Curve 16%
• Single Institution 16%
• Tumor Depth of Invasion 16%
• Tumor Extirpation 16%

Medicine and Dentistry

• Diseases 50%
• Health Care Cost 25%
• Malignant Neoplasm 50%
• Mouth Squamous Cell Carcinoma 100%
• Neck Dissection 75%
• Neoplasm 25%
• Nodal Metastasis 100%
• Oral Cavity 75%
• Primary Tumor 25%
• Sensitivity and Specificity 25%
• Squamous Cell Carcinoma 75%

Pharmacology, Toxicology and Pharmaceutical Science

• Diseases 66%
• Malignant Neoplasm 66%
• Mouth Squamous Cell Carcinoma 100%
• Neoplasm 33%
• Primary Tumor 33%
• Squamous Cell Carcinoma 100%