Artificial Intelligence in Healthcare

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 miningIllustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networksIncludes applications and case studies across all areas of AI in healthcare data INDICE: 1. Current healthcare data challenges 2. The rise in Artificial Intelligence 3. AI as a Tool in the analysis of healthcare data 4. Machine Learning: changing algorithms, models, and tools 5. Deep Learning: neural networks 6. Natural language processing 7. Privacy and Ethics Part II: Applications and Case Studies 8. Drug discovery data under AI application 9. Diagnostics and treatment decisions using AI application 10. Medical image analysis using AI application 11. Personalized medicine using AI application 12. AI assisted surgery 13. Smart healthcare 14. Telehealth and remote patient monitoring 15. Care management using AI applications 16. Future perspectives and outlook

• ISBN: 978-0-12-818438-7
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 350
• Fecha Publicación: 01/06/2020
• Nº Volúmenes: 1
• Idioma: Inglés