大葉大學圖書館 |

Machine learning and the internet of medical things in healthcare[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	610.2854678
書名/作者:	Machine learning and the internet of medical things in healthcare/ edited by Krishna Kant Singh, Mohamed Elhoseny, Akansha Singh, Ahmed A. Elngar.
其他作者:	Singh, Krishna Kant
出版者:	Amsterdam : : Academic Press,, 2021.
面頁冊數:	1 online resource.
附註:	Includes index.
標題:	Medical technology.
標題:	Machine learning.
標題:	Internet of things.
ISBN:	9780128232170 (electronic bk.)
ISBN:	9780128212295 (pbk.)
內容註:	1. Machine Learning Architecture and Framework 2. Machine Learning in Healthcare: Review, Opportunities and Challenges 3. Machine Learning for Biomedical Signal Processing 4. Artificial Intelligence in Medicine 5. Diagnosing of Disease Using Machine Learning 6. A Novel Approach of Telemedicine for Managing Fetal Condition based on Machine Learning Technology from Iot Based Wearable Medical Device 7. Iot Based Healthcare Delivery Services to Promote Transparency and Patient Satisfaction in a Corporate Hospital 8. Examining Diabetic Subjects on Their Correlation with TTH and CAD: A Statistical Approach on Exploratory Results 9. Cancer Prediction and Diagnosis Hinged on HCML in IOMT Environment 10. Parameterization Techniques for Automatic Speech Recognition System 11. Impact of Big Data in Healthcare System: A Quick Look into Electronic Health Record Systems.
摘要、提要註:	Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks.
電子資源:	https://www.sciencedirect.com/science/book/9780128212295

Machine learning and the internet of medical things in healthcare[electronic resource] /
Machine learning and the internet of medical things in healthcare[electronic resource] /edited by Krishna Kant Singh, Mohamed Elhoseny, Akansha Singh, Ahmed A. Elngar. - Amsterdam :Academic Press,2021. - 1 online resource.

Includes index.

1. Machine Learning Architecture and Framework 2. Machine Learning in Healthcare: Review, Opportunities and Challenges 3. Machine Learning for Biomedical Signal Processing 4. Artificial Intelligence in Medicine 5. Diagnosing of Disease Using Machine Learning 6. A Novel Approach of Telemedicine for Managing Fetal Condition based on Machine Learning Technology from Iot Based Wearable Medical Device 7. Iot Based Healthcare Delivery Services to Promote Transparency and Patient Satisfaction in a Corporate Hospital 8. Examining Diabetic Subjects on Their Correlation with TTH and CAD: A Statistical Approach on Exploratory Results 9. Cancer Prediction and Diagnosis Hinged on HCML in IOMT Environment 10. Parameterization Techniques for Automatic Speech Recognition System 11. Impact of Big Data in Healthcare System: A Quick Look into Electronic Health Record Systems.

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks.

ISBN: 9780128232170 (electronic bk.)

Nat. Bib. No.: GBC115975bnbSubjects--Topical Terms:

344017
Medical technology.
Index Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: R855.3

Dewey Class. No.: 610.2854678

Machine learning and the internet of medical things in healthcare[electronic resource] /
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505 0 $a 1. Machine Learning Architecture and Framework 2. Machine Learning in Healthcare: Review, Opportunities and Challenges 3. Machine Learning for Biomedical Signal Processing 4. Artificial Intelligence in Medicine 5. Diagnosing of Disease Using Machine Learning 6. A Novel Approach of Telemedicine for Managing Fetal Condition based on Machine Learning Technology from Iot Based Wearable Medical Device 7. Iot Based Healthcare Delivery Services to Promote Transparency and Patient Satisfaction in a Corporate Hospital 8. Examining Diabetic Subjects on Their Correlation with TTH and CAD: A Statistical Approach on Exploratory Results 9. Cancer Prediction and Diagnosis Hinged on HCML in IOMT Environment 10. Parameterization Techniques for Automatic Speech Recognition System 11. Impact of Big Data in Healthcare System: A Quick Look into Electronic Health Record Systems.
520 $a Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks.
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