Buch, Englisch, Band 843, 197 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 341 g
A Digital Revolution in Healthcare
Buch, Englisch, Band 843, 197 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 341 g
Reihe: Studies in Computational Intelligence
ISBN: 978-3-030-24411-8
Verlag: Springer International Publishing
This book highlights the latest advances in the application of artificial intelligence to healthcare and medicine. It gathers selected papers presented at the 2019 Health Intelligence workshop, which was jointly held with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the central issues, challenges, and potential opportunities in the field, along with new research results.
By addressing a wide range of practical applications, the book makes the emerging topics of digital health and precision medicine accessible to a broad readership. Further, it offers an essential source of information for scientists, researchers, students, industry professionals, national and international public health agencies, and NGOs interested in the theory and practice of digital and precision medicine and health, with an emphasis on risk factors in connection with disease prevention, diagnosis, and intervention.Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
Weitere Infos & Material
Preface.- Chapter 1. From Precision Medicine to Precision Health: A Full Angle from Diagnosis to Treatment and Prevention.- Chapter 2. Constructing Accurate Confidence Intervals when Aggregating Social Media Data for Public Health Monitoring.- Chapter 3. MCA-based Rule Mining Enables Interpretable Inference in Clinical Psychiatry.- Chapter 4. Automatic Exercise Recognition with Machine Learning, etc.
