Automatic detection of adverse events to predict drug label changes using text and data mining techniques

2013 ◽  
Vol 22 (11) ◽  
pp. 1189-1194 ◽  
Author(s):  
Harsha Gurulingappa ◽  
Luca Toldo ◽  
Abdul Mateen Rajput ◽  
Jan A. Kors ◽  
Adel Taweel ◽  
...  
Keyword(s):  
Data Mining ◽  
Adverse Events ◽  
Automatic Detection ◽  
Drug Label ◽  
Data Mining Techniques ◽  
Text And Data Mining

Text and Data Mining Techniques in Adverse Drug Reaction Detection

2015 ◽  
Vol 47 (4) ◽  
pp. 1-39 ◽  
Author(s):  
Sarvnaz Karimi ◽  
Chen Wang ◽  
Alejandro Metke-Jimenez ◽  
Raj Gaire ◽  
Cecile Paris
Keyword(s):  
Data Mining ◽  
Adverse Drug Reaction ◽  
Drug Reaction ◽  
Data Mining Techniques ◽  
Text And Data Mining

Data Mining Applications in the Service of e-Government

2012 ◽  
pp. 544-558 ◽  
Author(s):  
George Stylios ◽  
Dimitris Christodoulakis ◽  
Jeries Besharat ◽  
Maria-Alexandra Vonitsanou ◽  
Ioannis Kotrotsos ◽  
...  
Keyword(s):  
Data Mining ◽  
Public Sector ◽  
Added Value ◽  
Data Mining Techniques ◽  
Adaptation Capacity ◽  
Government Services ◽  
Current Trends ◽  
Text And Data Mining

In this chapter we propose the exploration of text and data mining techniques for empowering e-government applications and services for the citizen’s benefit. In particular, we start by providing a field overview with respect to the current trends in e-government services and we demonstrate via proofs of concept the limited adaptation existing e-government applications entail. Stimulated by the need to transform e-government services to e-inclusion applications, we suggest the utilization of data mining techniques for processing the governmental data so as to extract and associate information fragments with real citizen needs and thus enable the encapsulation of the latter in future governmental decisions. To demonstrate the usability and added value of our proposed approach we have designed an interactive e-government infrastructure, the architecture of which we will present and discuss in our chapter. Moreover, we will elaborate on the system details, its adaptation capacity and we will discuss its usage benefits for both citizens and public sector bodies.

Data Mining Applications in the Service of e-Government

2013 ◽  
pp. 392-407
Author(s):  
George Stylios ◽  
Dimitris Christodoulakis ◽  
Jeries Besharat ◽  
Maria-Alexandra Vonitsanou ◽  
Ioannis Kotrotsos ◽  
...  
Keyword(s):  
Data Mining ◽  
Public Sector ◽  
Added Value ◽  
Data Mining Techniques ◽  
Adaptation Capacity ◽  
Government Services ◽  
Current Trends ◽  
Text And Data Mining

In this chapter we propose the exploration of text and data mining techniques for empowering e-government applications and services for the citizen’s benefit. In particular, we start by providing a field overview with respect to the current trends in e-government services and we demonstrate via proofs of concept the limited adaptation existing e-government applications entail. Stimulated by the need to transform e-government services to e-inclusion applications, we suggest the utilization of data mining techniques for processing the governmental data so as to extract and associate information fragments with real citizen needs and thus enable the encapsulation of the latter in future governmental decisions. To demonstrate the usability and added value of our proposed approach we have designed an interactive e-government infrastructure, the architecture of which we will present and discuss in our chapter. Moreover, we will elaborate on the system details, its adaptation capacity and we will discuss its usage benefits for both citizens and public sector bodies.

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