Buch, Englisch, 310 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 730 g
Theory and Practice
Buch, Englisch, 310 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 730 g
ISBN: 978-0-12-820203-6
Verlag: William Andrew Publishing
The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in the healthcare sector is to come up with ways to provide personalized healthcare to patients by taking into account the enormous amounts of already existing data.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
Weitere Infos & Material
1.Big Data classification: techniques and tools 2.Big Data Analytics for healthcare: theory and applications 3.Application of tools and techniques of Big data analytics for healthcare system 4.Healthcare and medical Big Data analytics 5.Big Data analytics in medical imaging 6.Big Data analytics and artificial intelligence in mental healthcare 7.Big Data based breast cancer prediction using kernel support vector machine with the Gray Wolf Optimization algorithm 8.Big Data based medical data classification using oppositional Gray Wolf Optimization with kernel ridge regression 9.An analytical hierarchical process evaluation on parameters Apps-based Data Analytics for healthcare services 10.Firefly-Binary Cuckoo Search Technique based heart disease prediction in Big Data Analytics 11.Hybrid technique for heart diseases diagnosis based on convolution neural network and long short-term memory