Big data in otolaryngology / edited by Jennifer A. Villwock.

Format:

Book

Contributor:

Villwock, Jennifer A., editor.

Language:

English

Subjects (All):

Otolaryngology--Data processing.

Otolaryngology.

Big data.

Medical informatics.

Otorhinolaryngologic Diseases--data processing.

Medical Informatics Applications.

Medical Informatics.

Medical Subjects:

Otorhinolaryngologic Diseases--data processing.

Medical Informatics Applications.

Medical Informatics.

Physical Description:

1 online resource (x, 147 pages) : illustrations

Place of Publication:

St. Louis, Missouri : Elsevier, [2024]

System Details:

data file

Summary:

"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."--provided by Publisher.

Contents:

Chapter 1. Big data

Science fiction or clinically relevant?

Chapter 2. Large administrative datasets: Lessons and limitations

Chapter 3. Sources of high-dimensional data

The electronic health record, health systems, and insurance and payor data

Chapter 4. Best practices when interpreting big data studies: Considerations and red flags

Chapter 5. Current big data approaches to clinical questions in otolaryngology

Chapter 6. Bias in big data: Historically underrepresented groups and implications

Chapter 7. Artificial intelligence in otolaryngology

Chapter 8. The patient perspective on big data and its use in clinical care.

Notes:

Includes bibliographical references and index.

Description based upon online resource; title from PDF title page (viewed Sept. 6, 2024).

Other Format:

Print version:

Print version: Big data in otolaryngology.

ISBN:

9780443105210

0443105219

OCLC:

1450093514

Access Restriction:

Restricted for use by site license.