Big Data in Otolaryngology

Coordinator: Villwock Jennifer A.

Language: English
Cover of the book Big Data in Otolaryngology

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250 p. · 19x23.3 cm · Paperback
Big data plays an increasingly important role in today's practice of otolaryngology and in all of healthcare. In Big Data in Otolaryngology, Dr. Jennifer Villwock leads a team of expert authors who provide a comprehensive view of many key impacts of big data in otolaryngology-including understanding what big data is and what we can and cannot learn from it; best practices regarding analysis; translating findings to clinical care and associated cautions; ethical issues; and future directions.
  • Covers the clinical relevance of big data in otolaryngology, lessons and limitations of large administrative datasets, biologic big data, and much more.

  • Discusses artificial intelligence (AI) in otolaryngology and its clinical application.

  • Presents a patient perspective on big data in otolaryngology and its use in clinical care, as well as a glimpse into the future of big data.

  • Compiles the knowledge and expertise of leading experts in the field who have assembled the most up-to-date recommendations for managing big data in otolaryngology.

  • Consolidates today's available information on this timely topic into a single, convenient resource.

1. Introduction: Big Data - Science Fiction or Clinically Relevant?2. Large Administrative Datasets: Lessons and Limitations3. Biologic Big Data: Introduction to Genomics, Proteomics, and Metabolomics4. Sources of High-Dimensional Data - The Electronic Health Record, Health Systems, and Insurance and Payor Data5. Best Practices When Interpreting Big Data Studies: Considerations and Red Flags6. Current Big Data Approaches to Clinical Questions in Otolaryngology7. Translating Big Data to Patient Care8. Bias in Big Data: Historically Underrepresented Groups and Implications9. Artificial Intelligence in Otolaryngology 10. Clinical Applications of Artificial Intelligence: Clinical Decision Aids, Imaging Analysis, and Disease Prediction11. The Patient Perspective on Big Data and Its Use in Clinical Care