Big Data in Otolaryngology
- 1 Edición - 17 de julio de 2024
- Última edición
- Editor: Jennifer A. Villwock
- Idioma: Inglés
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… Leer más
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
Otolaryngologists in practice
1. Big data - Science fiction or clinically relevant
2. Large administrative datasets: Lessons and limitations
3. Sources of high-dimensional data - The electronic health record, health systems, and insurance and payor data
4. Best practices when interpreting big data studies: Considerations and red flags
5. Current big data approaches to clinical questions in otolaryngology
6. Bias in big data: Historically underrepresented groups and implications
7. Artificial intelligence in otolaryngology
8. The patient perspective on big data and its use in clinical care
2. Large administrative datasets: Lessons and limitations
3. Sources of high-dimensional data - The electronic health record, health systems, and insurance and payor data
4. Best practices when interpreting big data studies: Considerations and red flags
5. Current big data approaches to clinical questions in otolaryngology
6. Bias in big data: Historically underrepresented groups and implications
7. Artificial intelligence in otolaryngology
8. The patient perspective on big data and its use in clinical care
- Edición: 1
- Última edición
- Publicado: 17 de julio de 2024
- Idioma: Inglés
JV
Jennifer A. Villwock
Afiliaciones y experiencia
Associate Professor, Otolaryngology-Head and Neck Surgery, The University of Kansas Medical Center, Kansas City, Kansas, USALee Big Data in Otolaryngology en ScienceDirect