Machine Learning, Big Data, and IoT for Medical Informatics
- Indbinding:
- Paperback
- Sideantal:
- 458
- Udgivet:
- 16. juni 2021
- Størrelse:
- 236x190x30 mm.
- Vægt:
- 938 g.
- 2-3 uger.
- 11. december 2024
På lager
Normalpris
Abonnementspris
- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Machine Learning, Big Data, and IoT for Medical Informatics
Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics.
In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data.
This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.
Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems.Includes several privacy preservation techniques for medical data.Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis.Offers case studies and applications relating to machine learning, big data, and health care analysis.
In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data.
This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.
Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems.Includes several privacy preservation techniques for medical data.Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis.Offers case studies and applications relating to machine learning, big data, and health care analysis.
Brugerbedømmelser af Machine Learning, Big Data, and IoT for Medical Informatics
Giv din bedømmelse
For at bedømme denne bog, skal du være logget ind.Andre købte også..
Find lignende bøger
Bogen Machine Learning, Big Data, and IoT for Medical Informatics findes i følgende kategorier:
© 2024 Pling BØGER Registered company number: DK43351621