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Artificial Intelligence in Precision Health. From Concept to Applications

  • Book

  • March 2020
  • Elsevier Science and Technology
  • ID: 4806634

Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand artificial intelligence and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Additionally, there is a section dedicated to discuss and analyze AI products related to precision healthcare already available.

This book is a valuable source for clinicians, healthcare workers, and researchers from diverse areas of biomedical field who may or may not have computational background and want to learn more about the innovative field of artificial intelligence for precision health.

Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.

Table of Contents

Section 1: Artificial Intelligence Technologies1. Interpretable Artificial Intelligence: Addressing the Adoption Gap in Medicine2. Artificial Intelligence methods in computer-aided diagnostic tools and decision support analytics for clinical informatics3. Deep learning in Precision Medicine4. Machine learning systems and precision medicine: a conceptual and experimental approach to single individual statistics5. Machine learning in digital health, recent trends and on-going challenges6. Data Mining to Transform Clinical and Translational Research Findings into Precision Health

Section II: Applications and Precision Systems/Application of Artificial Intelligence7. Predictive Models in Precision Medicine8. Deep Neural Networks for Phenotype Prediction: Application to rare diseases9. Artificial Intelligence in the management of patients with intracranial neoplasms10. Artificial Intelligence to aid the early detection of Mental Illness11. Use of Artificial Intelligence in Alzheimer Disease Detection12. Artificial Intelligence to predict atheroma plaque vulnerability13. Decision support systems in cardiovascular medicine through artificial intelligence: applications in the diagnosis of infarction and prognosis of heart failure14. Artificial Intelligence for Decision Support Systems in Diabetes15. Clinical decision support systems to improve the diagnosis and management of respiratory diseases16. Use of Artificial Intelligence in Neurosurgery and Otorhinolaryngology (Head and Neck Surgery)17. Use of Artificial Intelligence in Emergency Medicine18. Use of Artificial Intelligence in Infectious diseases19. Artificial Intelligence techniques applied to patient care and monitoring20. Use of artificial intelligence in precision nutrition and fitness

Section III: Precision Systems21. Artificial Intelligence in Precision health: Systems in practice

Authors

Debmalya Barh Federal University of Minas Gerais, Belo Horizonte, Brazil. Dr. Debmalya Barh is currently a Visiting Full Professor (Titular, Grade-E) in Bioinformatics and Precision Health at the Department of Genetics, Ecology, and Evolution, ICB, Federal University of Minas Gerais, Brazil and honorary scientist of the Institute of Integrative Omics and Applied Biotechnology (IIOAB), India. With over 20 years of experience, he has led academic, healthcare, molecular diagnostic, and bioinformatics industry endeavors. He works with more than 400 scientists from 100+ top ranked organizations across 40+ countries and has 220+ publications and a branded editor for 10+ cutting-edge omics related reference books. He is an expert in in precision/personalized health and integrative omics-based biomarker and target discovery in infectious and complex lifestyle diseases.