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...
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| Other Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
[Erscheinungsort nicht ermittelbar]
Academic Press
2021
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| Series: | Intelligent data centric systems
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| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9780128217818/?ar |
| Summary: | 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. |
| Physical Description: | 1 Online-Ressource. |
| ISBN: | 9780128217818 0128217812 |
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| spelling | Machine learning, big data, and IoT for medical informatics edited by Pardeep Kumar, Yugal Kumar and Mohamed A. Tawhid [Erscheinungsort nicht ermittelbar] Academic Press 2021 1 Online-Ressource. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intelligent data centric systems 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. Machine learning Medical informatics Artificial intelligence Medical applications Medicine Data processing Medical Informatics Medical Informatics Applications Machine Learning Apprentissage automatique Médecine ; Informatique Intelligence artificielle en médecine Medicine ; Data processing Artificial intelligence ; Medical applications Kumar, Pardeep 1976- MitwirkendeR ctb Kumar, Yugal MitwirkendeR ctb Tawhid, Mohamed A. MitwirkendeR ctb 0128217774 Erscheint auch als Druck-Ausgabe 0128217774 |
| spellingShingle | Machine learning, big data, and IoT for medical informatics Machine learning Medical informatics Artificial intelligence Medical applications Medicine Data processing Medical Informatics Medical Informatics Applications Machine Learning Apprentissage automatique Médecine ; Informatique Intelligence artificielle en médecine Medicine ; Data processing Artificial intelligence ; Medical applications |
| title | Machine learning, big data, and IoT for medical informatics |
| title_auth | Machine learning, big data, and IoT for medical informatics |
| title_exact_search | Machine learning, big data, and IoT for medical informatics |
| title_full | Machine learning, big data, and IoT for medical informatics edited by Pardeep Kumar, Yugal Kumar and Mohamed A. Tawhid |
| title_fullStr | Machine learning, big data, and IoT for medical informatics edited by Pardeep Kumar, Yugal Kumar and Mohamed A. Tawhid |
| title_full_unstemmed | Machine learning, big data, and IoT for medical informatics edited by Pardeep Kumar, Yugal Kumar and Mohamed A. Tawhid |
| title_short | Machine learning, big data, and IoT for medical informatics |
| title_sort | machine learning big data and iot for medical informatics |
| topic | Machine learning Medical informatics Artificial intelligence Medical applications Medicine Data processing Medical Informatics Medical Informatics Applications Machine Learning Apprentissage automatique Médecine ; Informatique Intelligence artificielle en médecine Medicine ; Data processing Artificial intelligence ; Medical applications |
| topic_facet | Machine learning Medical informatics Artificial intelligence Medical applications Medicine Data processing Medical Informatics Medical Informatics Applications Machine Learning Apprentissage automatique Médecine ; Informatique Intelligence artificielle en médecine Medicine ; Data processing Artificial intelligence ; Medical applications |
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