Περιεχόμενα
1. Introduction: Big Data – Science Fiction or Clinically Relevant?
2. Large Administrative Datasets: Lessons and Limitations
3. Biologic Big Data: Introduction to Genomics, Proteomics, and Metabolomics
4. Sources of High-Dimensional Data – The Electronic Health Record, Health Systems, and Insurance and Payor Data
5. Best Practices When Interpreting Big Data Studies: Considerations and Red Flags
6. Current Big Data Approaches to Clinical Questions in Otolaryngology
7. Translating Big Data to Patient Care
8. Bias in Big Data: Historically Underrepresented Groups and Implications
9. Artificial Intelligence in Otolaryngology
10. Clinical Applications of Artificial Intelligence: Clinical Decision Aids, Imaging Analysis, and Disease Prediction
11. The Patient Perspective on Big Data and Its Use in Clinical Care