|Author||Karimi, Sarvnaz ♦ Wang, Chen ♦ Metke-Jimenez, Alejandro ♦ Gaire, Raj ♦ Paris, Cecile|
|Source||ACM Digital Library|
|Publisher||Association for Computing Machinery (ACM)|
|Subject Domain (in DDC)||Computer science, information & general works ♦ Data processing & computer science|
|Subject Keyword||Drug side effect ♦ Adverse drug reaction ♦ Data mining ♦ Drug safety ♦ Signal detection ♦ Statistical analysis ♦ Text mining|
|Abstract||We review data mining and related computer science techniques that have been studied in the area of drug safety to identify signals of adverse drug reactions from different data sources, such as spontaneous reporting databases, electronic health records, and medical literature. Development of such techniques has become more crucial for public heath, especially with the growth of data repositories that include either reports of adverse drug reactions, which require fast processing for discovering signals of adverse reactions, or data sources that may contain such signals but require data or text mining techniques to discover them. In order to highlight the importance of contributions made by computer scientists in this area so far, we categorize and review the existing approaches, and most importantly, we identify areas where more research should be undertaken.|
|Age Range||18 to 22 years ♦ above 22 year|
|Education Level||UG and PG|
|Learning Resource Type||Article|
|Publisher Place||New York|
|Journal||ACM Computing Surveys (CSUR)|
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