Buch, Englisch, 264 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g
Buch, Englisch, 264 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g
ISBN: 978-1-032-85348-2
Verlag: Taylor & Francis Ltd
There have been very significant technological advancements made in the healthcare industry in recent decades. They have not only helped us better comprehend the morphology and physiology of the various organs that make up the human body but have also advanced the diagnosis and, consequently, the treatment of several diseases in a variety of medical specialties from very early stages. The advancements in artificial intelligence (AI) and computer vision (CV) have primarily made this possible. In a nutshell, these tools enable us to collect, process, interpret, and analyze a limitless quantity of static and dynamic medical data in real-time, which will improve the way each disease is characterized and the patients that are chosen. Many potentially fatal illnesses, such as COVID-19, pneumonia, and cancer, can be cured if diagnosed in the initial stages very early on. Computer-based medical imaging techniques, such as CT scans and X-rays, can be useful in detecting all of these illnesses. On the other hand, various brain anomalies and heart diseases can also be anticipated using biological signals, like electroencephalography (EEG), electrocardiogram (ECG) etc. Application of machine learning can make the predictions of these diseases more accurate. and help the clinician to detect appropriate ones. This helps in faster recognition of disease as well as with the intervention of the technology, makes it feasible to spread to remote places. The goal is to create machine learning algorithms that aid in the analysis of diverse medical data and the prediction of diseases based on the characteristics of the data.
Zielgruppe
Academic and Postgraduate
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
Weitere Infos & Material
The proposed book will contain chapters corresponding to the following themes but not limited to
1. Machine Intelligence Systems and Technologies
2. Deep Learning Applications
3. AI and Data Science
4. Next Generation Computing and Applications
5. Emerging Technologies
6. Artificial Neural Networks
7. Ambient Intelligence
8. Hybrid Intelligent Systems
9. Robotics and Cybernetics
10. Biomedical Data Analysis
11. Cognitive Computing
12. Computational Intelligence
13. Video Surveillance and Related Applications
14. Nature Inspired Computing Techniques
15. Image Processing
16. Pattern Recognition and Applications
17. Human Computer Interaction
18. Natural Language Processing
19. Recommendation Systems
20. Data Mining
21. Web Mining
22. ML and DL Applications for Healthcare
23. Internet of Things (IoT)
24. Computer Vision
25. Smart and Intelligent Sensors
26. Soft Computing
27. Spatial Data Analysis
28. Speech and Audio Processing Applications
29. Reinforcement Learning
30. Transfer Learning