What is the potential of machine learning to improve the diagnostic capabilities of chest radiographs in cases of pediatric foreign body aspiration (FBA)?
Novel Machine Learning Predicts Oral Squamous Cell Carcinoma Recurrence Timing
Machine learning methods can interpret complex patterns of patient, clinicopathological, and treatment factors to predict timing of oral squamous cell carcinoma recurrence.
There’s Room for Improvement in Machine Learning Publication Standards within Otolaryngology
What is the status of existing reporting guidelines for machine learning (ML) in biomedical publications and present recommendations for their use in otolaryngology journal reports? BOTTOM LINE There is limited […]
Artificial Intelligence and Machine Learning in Otolaryngology
While use of artificial intelligence in otolaryngology is in its infancy, the benefits of employing these technologies show great promise.