A supervised machine learning model for identifying predictive factors for recommending head and neck cancer surgery.
Max L JiamKevin Z XinPatrick K HaNicole T JiamPublished in: Head & neck (2024)
ML modeling accurately predicts head and neck cancer surgery recommendations based on patient and cancer information from a large population-based dataset. ML adjuncts for referral processing may decrease the time to treatment for patients with cancer.
Keyphrases
- machine learning
- minimally invasive
- coronary artery bypass
- surgical site infection
- papillary thyroid
- primary care
- artificial intelligence
- case report
- big data
- healthcare
- deep learning
- health information
- clinical practice
- squamous cell
- percutaneous coronary intervention
- young adults
- atrial fibrillation
- childhood cancer
- smoking cessation