An amalgamation of blockchain, Internet of Medical Things and 5G technologies for the Healthcare 4.0 ecosystem

2021 ◽  
pp. 397-450
Author(s):  
Desai Karanam Sreekantha ◽  
R. V. Kulkarni
Keyword(s):  
5G Technologies ◽  
Internet Of Medical Things

Mutual Authentication Scheme for the Device-to-Server Communication in the Internet of Medical Things

2021 ◽  
pp. 1-1
Author(s):  
Jiangfeng Sun ◽  
Fazlullah Khan ◽  
Junxia Li ◽  
Mohammad Dahman Alshehri ◽  
Ryan Alturki ◽  
...  
Keyword(s):  
Mutual Authentication ◽  
Authentication Scheme ◽  
The Internet ◽  
Internet Of Medical Things

scholarly journals A Generative Adversarial Network (GAN) Technique for Internet of Medical Things Data

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3726
Author(s):  
Ivan Vaccari ◽  
Vanessa Orani ◽  
Alessia Paglialonga ◽  
Enrico Cambiaso ◽  
Maurizio Mongelli
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Monitoring Program ◽  
Clinical Decision Support Systems ◽  
Direct Access ◽  
Generative Adversarial Networks ◽  
Chronic Obstructive ◽  
Generative Adversarial Network ◽  
Internet Of Medical Things ◽  
Synthetic Datasets

The application of machine learning and artificial intelligence techniques in the medical world is growing, with a range of purposes: from the identification and prediction of possible diseases to patient monitoring and clinical decision support systems. Furthermore, the widespread use of remote monitoring medical devices, under the umbrella of the “Internet of Medical Things” (IoMT), has simplified the retrieval of patient information as they allow continuous monitoring and direct access to data by healthcare providers. However, due to possible issues in real-world settings, such as loss of connectivity, irregular use, misuse, or poor adherence to a monitoring program, the data collected might not be sufficient to implement accurate algorithms. For this reason, data augmentation techniques can be used to create synthetic datasets sufficiently large to train machine learning models. In this work, we apply the concept of generative adversarial networks (GANs) to perform a data augmentation from patient data obtained through IoMT sensors for Chronic Obstructive Pulmonary Disease (COPD) monitoring. We also apply an explainable AI algorithm to demonstrate the accuracy of the synthetic data by comparing it to the real data recorded by the sensors. The results obtained demonstrate how synthetic datasets created through a well-structured GAN are comparable with a real dataset, as validated by a novel approach based on machine learning.

EWPS: Emergency data communication in the Internet of Medical Things

2021 ◽  
pp. 1-1
Author(s):  
S. Gopikrishnan ◽  
P. Priakanth ◽  
Gautam Srivastava ◽  
Giancarlo Fortino
Keyword(s):  
Data Communication ◽  
The Internet ◽  
Internet Of Medical Things

scholarly journals On the internet of medical things

2020 ◽  
Vol 63 (8) ◽  
pp. 5-5
Author(s):  
Vinton G. Cerf
Keyword(s):  
The Internet ◽  
Internet Of Medical Things
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