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.

In this issue of Otolaryngologic Clinics, guest editors Stephen P. Cragle and Eileen H. Dauer bring their considerable expertise to the topic of Business of Otolaryngology. Top experts in the field cover key topics such as Committing Otolaryngology to pay equity and diversity, Coding for optimal payment, E-health & Telemedicine in Otolaryngology, and more. - Contains 15 relevant, practice-oriented topics including Making a major change – changing your practice setting, retirement, and locums; Talking to patients and their families about adverse events – how transparency and empathy can be transformative for all (Michigan Model or CANDOR); Entrepreneurship and Innovation in Otolaryngology; and more. - Provides in-depth clinical reviews on the Business of Otolaryngology, offering actionable insights for clinical practice. - Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.

In this issue of Otolaryngologic Clinics, guest editors Drs. Anais Rameau and Matthew G. Crowson bring their considerable expertise to the topic of Artificial Intelligence in Otolaryngology. Top experts in the field cover timely topics in the areas of Best Practices, AI Modalities, Implementation and Governance, and Subspecialty AI. - Contains 17 relevant, practice-oriented topics including clinical data/machine learning; generative AI and otolaryngology-head and neck surgery; ethics; AI in otology and neurotology; AI in facial plastic and reconstructive surgery; AI in pediatric otolaryngology; and more. - Provides in-depth clinical reviews on artificial intelligence in otolaryngology, offering actionable insights for clinical practice. - Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.

March 04-05, 2019, Barcelona, Spain Key Topics: Big Data Analytics ,Big Data Algorithms ,Big Data In Bioinformatics ,Data Mining With Big Data ,Visualization In Big Data ,Big Data In Neural Network For Deep Learning ,High Performance Computing For Big Data ,Machine Learning In Data Science ,Open Science In Big Data ,Hadoop Map-Reduce For Analyzing Information ,Regression In Data Science ,Big Data Applications

Big Data Analytics and Intelligence is essential reading for researchers and experts working in the fields of health care, data science, analytics, the internet of things, and information retrieval.

Through four editions, Cummings Otolaryngology has been the world's most trusted source for comprehensive guidance on all facets of head and neck surgery. This 5th Edition - edited by Paul W. Flint, Bruce H. Haughey, Valerie J. Lund, John K. Niparko, Mark A. Richardson, K. Thomas Robbins, and J. Regan Thomas – equips you to implement all the newest discoveries, techniques, and technologies that are shaping patient outcomes. You'll find new chapters on benign neoplasms, endoscopic DCR, head and neck ultrasound, and trends in surgical technology... a new section on rhinology... and coverage of hot topics such as Botox. Plus, your purchase includes access to the complete contents of this encyclopedic reference online, with video clips of key index cases! Overcome virtually any clinical challenge with detailed, expert coverage of every area of head and neck surgery, authored by hundreds of leading luminaries in the field. See clinical problems as they present in practice with 3,200 images - many new to this edition. Consult the complete contents of this encyclopedic reference online, with video clips of key index cases! Stay current with new chapters on benign neoplasms, endoscopic DCR, head and neck ultrasound, and trends in surgical technology... a new section on rhinology... and coverage of hot topics including Botox. Get fresh perspectives from a new editorial board and many new contributors. Find what you need faster through a streamlined format, reorganized chapters, and a color design that expedites reference.

This state-of-the-art Handbook provides an overview of the role of big data analytics in various areas of business and commerce, including accounting, finance, marketing, human resources, operations management, fashion retailing, information systems, and social media. It provides innovative ways of overcoming the challenges of big data research and proposes new directions for further research using descriptive, diagnostic, predictive, and prescriptive analytics.

Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers

This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.