Application of Artificial Intelligence to Overcome Clinical Information Overload in Urologic Cancer.
Arnulf StenzlCora N SternbergJenny GhithLucile SerfassBob J A SchijvenaarsAndrea SbonerPublished in: BJU international (2021)
As the literature and clinical trial landscape continues to grow in complexity and with increasing speed, the ability to pull the right information at the right time from different search engines and resources while excluding social media bias becomes more challenging. This review demonstrates that by applying natural language processing and machine learning algorithms, validated and optimized AI leads to a speedier, more personalized, efficient and focused search compared with traditional methods.
Keyphrases
- artificial intelligence
- machine learning
- social media
- health information
- clinical trial
- big data
- deep learning
- papillary thyroid
- systematic review
- squamous cell
- study protocol
- single cell
- autism spectrum disorder
- phase ii
- open label
- randomized controlled trial
- lymph node metastasis
- squamous cell carcinoma
- childhood cancer