scholarly journals IEEE Access Special Section Editorial: Advanced Information Sensing and Learning Technologies for Data-Centric Smart Health Applications

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 30404-30407
Author(s):  
Qingxue Zhang ◽  
Vincenzo Piuri ◽  
Edward A. Clancy ◽  
Dian Zhou ◽  
Thomas Penzel ◽  
...  
Author(s):  
Angelo Capossele ◽  
Andrea Gaglione ◽  
Michele Nati ◽  
Mauro Conti ◽  
Riccardo Lazzeretti ◽  
...  

2019 ◽  
Vol 5 ◽  
pp. 205520761986946
Author(s):  
Emily de Redon ◽  
Amanda Centi

The health sector has been slow to adopt and integrate new technological advances into antiquated workflows and processes. The onset of smart health applications and devices has initiated a push for healthcare systems as well as physicians to incorporate and utilize such technology and the big data it collects. However, without considering the challenges experienced in large-scale trials, physicians and their clinics will run into similar barriers to implementation and uptake. Thoughtful implementation and preparation will make the use of such technological advances possible, palatable and effective in improving clinical care.


2021 ◽  
pp. 283-296
Author(s):  
Benedikt Schnell ◽  
Patrick Moder ◽  
Hans Ehm ◽  
Marcel Konstantinov ◽  
Mahmoud Ismail

2020 ◽  
Vol 10 (1) ◽  
pp. 18-20
Author(s):  
Gustavo Ramírez González

2019 ◽  
Vol 11 (19) ◽  
pp. 2216
Author(s):  
Xin Huang ◽  
Jiayi Li ◽  
Francesca Bovolo ◽  
Qi Wang

This special issue hosts papers on change detection technologies and analysis in remote sensing, including multi-source sensors, advanced machine learning technologies for change information mining, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multi-source remote sensed data was used in change detection.


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