Artificial Intelligence in Healthcare / edited by Adam Bohr, Kaveh Memarzadeh.

Format:

Book

Contributor:

Bohr, Adam, editor.

Memarzadeh, Kaveh, editor.

Language:

English

Subjects (All):

Artificial intelligence.

Physical Description:

1 online resource (xxvii, 355 pages). : illustrations

Place of Publication:

London : Academic Press, imprint of Elsevier, 2020.

Summary:

Artificial Intelligence in Healthcare Data is more than a comprehensive introduction to artificial intelligence and machine learning as tools in the generation and analysis of healthcare data. The book is split into two sections with an introduction to current healthcare data challenges followed by specific applications and case studies. In the first section, the editors explore how AI is used as a tool in the analysis of healthcare data, specifically focusing on machine learning, deep learning, and natural language processing. They take a deep dive into data privacy, cybersecurity, and the ethics of data sharing. In the second section, expert chapter authors explore how AI tools can help to interrogate data across a range of healthcare applications including AI driven wearables and sensors and AI assisted surgery. This book will be useful for researchers, graduate students, and practitioners in computer science, data science, bioinformatics, health informatics, biomedical engineering, and clinical engineering.TABLE OF CONTENTSBlue sections added by editors as NEW or "clarification of chapter content" based on reviewer feedbackPart I: Introduction and Tools (Adam Bohr and Sabine Hauert)Current healthcare data challengesBias and dataset collectionData quality and data management and analysisThe rise in Artificial IntelligenceAI as a Tool in the analysis of healthcare dataMachine Learning: changing algorithms, models, and toolsDeep Learning: neural networks Natural language processingPrivacy and EthicsInformation sharing, data access, and block chains Data Governance and data protectionCybersecurityImpact of AI on healthcare insurances and policiesPart II: Applications and Case Studies Drug discovery data under AI application (Kaveh Memarzadeh, UCL)Diagnostics and treatment decisions using AI application (Dinesh Dyas, Washington Univ, St. Louis)Medical image analysis using AI application (Saurbh Jha, U of Pennsylvania)Personalized medicine using AI application (Umang Patel, Babylon)AI assisted surgery (Dominic King, UCL)Smart healthcare (TBA)AI driven wearables and sensorsSmart hospitals: interoperabilitySmart homesTelehealth and remote patient monitoring (TBA)Care management using AI applications (Lydia Drumright, Cambridge)Future perspectives and outlook (Bohr/Hauert) Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Notes:

Includes indexes.

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

ISBN:

9780128184387

0128184388