This table was constructed using the data in our previous reports [ 192022 - 26 ], and the permission of replication was obtained from the publishers. Advantages of FAERS data mining It is well-accepted that a randomized, prospective, large-scale and long-term clinical trial is the best way to assess the association between a drug and an adverse event; however, such trials are not practical due to great expenses of time and cost, especially for rare but clinically important adverse events [ 4647 ]. Data mining of the FAERS database might provide previously unknown, but clinically important associations, and give us useful suggestions to guide clinical decision making.
Data mining is used wherever there is digital data available today. Notable examples of data mining can be found throughout business, medicine, science, and surveillance. Privacy concerns and ethics[ edit ] While the term "data mining" itself may have no ethical implications, it is often associated with the mining of information in relation to peoples' behavior ethical and otherwise.
A common way for this to occur is through data aggregation.
Data aggregation involves combining data together possibly from various sources in Top 10 data mining case studies way that facilitates analysis but that also might make identification of private, individual-level data deducible or otherwise apparent. The threat to an individual's privacy comes into play when the data, once compiled, cause the data miner, or anyone who has access to the newly compiled data set, to be able to identify specific individuals, especially when the data were originally anonymous.
Data may also be modified so as to become anonymous, so that individuals may not readily be identified. This indiscretion can cause financial, emotional, or bodily harm to the indicated individual.
In one instance of privacy violation, the patrons of Walgreens filed a lawsuit against the company in for selling prescription information to data mining companies who in turn provided the data to pharmaceutical companies.
Safe Harbor Principles currently effectively expose European users to privacy exploitation by U. As a consequence of Edward Snowden 's global surveillance disclosurethere has been increased discussion to revoke this agreement, as in particular the data will be fully exposed to the National Security Agencyand attempts to reach an agreement have failed.
The HIPAA requires individuals to give their "informed consent" regarding information they provide and its intended present and future uses. More importantly, the rule's goal of protection through informed consent is approach a level of incomprehensibility to average individuals.
Use of data mining by the majority of businesses in the U. Copyright law[ edit ] Situation in Europe[ edit ] Due to a lack of flexibilities in European copyright and database lawthe mining of in-copyright works such as web mining without the permission of the copyright owner is not legal.
Where a database is pure data in Europe there is likely to be no copyright, but database rights may exist so data mining becomes subject to regulations by the Database Directive. On the recommendation of the Hargreaves review this led to the UK government to amend its copyright law in  to allow content mining as a limitation and exception.
Only the second country in the world to do so after Japan, which introduced an exception in for data mining. However, due to the restriction of the Copyright Directivethe UK exception only allows content mining for non-commercial purposes.
UK copyright law also does not allow this provision to be overridden by contractual terms and conditions. The European Commission facilitated stakeholder discussion on text and data mining inunder the title of Licences for Europe.
As content mining is transformative, that is it does not supplant the original work, it is viewed as being lawful under fair use. For example, as part of the Google Book settlement the presiding judge on the case ruled that Google's digitisation project of in-copyright books was lawful, in part because of the transformative uses that the digitisation project displayed - one being text and data mining.
Data mining and machine learning software. Public access to application source code is also available. Text and search results clustering framework. A chemical structure miner and web search engine.
The Konstanz Information Miner, a user friendly and comprehensive data analytics framework. MEPX - cross platform tool for regression and classification problems based on a Genetic Programming variant.
A software package that enables users to integrate with third-party machine-learning packages written in any programming language, execute classification analyses in parallel across multiple computing nodes, and produce HTML reports of classification results.
A suite of libraries and programs for symbolic and statistical natural language processing NLP for the Python language. Open neural networks library. A component-based data mining and machine learning software suite written in the Python language. A programming language and software environment for statistical computing, data mining, and graphics.
It is part of the GNU Project. An open-source deep learning library for the Lua programming language and scientific computing framework with wide support for machine learning algorithms.
A suite of machine learning software applications written in the Java programming language. Proprietary data-mining software and applications[ edit ] The following applications are available under proprietary licenses.Data Mining Case Studies and Practice Prize is an international peer-reviewed workshop highlighting successful real-world applications of data yunusemremert.com date: 08 Dec, Top Data Mining Case Studies panel at ICDM'10 will present the top 10 data mining case studies submissions by ten of the top data miners in the field.
Following the successes of the 10 Challenging Problems in Data Mining Research at ICDM '05 and the Top 10 Algorithms in Data Mining at ICDM ' Downloadable DMCS Proceedings - Download Data Mining Case Studies I - DMCS I, held at the Fifth IEEE International Conference on Data Mining (ICDM ) in Houston, Texas.
We report on the panel discussion held at the ICDM'10 conference on the top 10 data mining case studies in order to provide a snapshot of where and how data mining techniques have made significant real-world impact. Big data and analytics are driving vast improvements in patient care and provider efficiencies.
Below are 10 case studies Health Data Management ran in the past year. Takiwā secures data and platform, migrating to onshore IBM Cloud. Takiwā secures data and platform, migrating to onshore IBM Cloud. Takiwā is currently working to address challenges in sectors like health, education, culture and identity, social and environmental well-being and economic development.