scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Text and Data Mining Techniques in Adverse Drug Reaction Detection

TL;DR: In order to highlight the importance of contributions made by computer scientists in this area so far, the existing approaches are categorized and review, and most importantly, areas where more research should be undertaken are identified.
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.
Citations
More filters
01 Jan 2016
TL;DR: The counting processes and survival analysis is universally compatible with any devices to read and is available in the digital library an online access to it is set as public so you can get it instantly.
Abstract: Thank you very much for reading counting processes and survival analysis. Maybe you have knowledge that, people have search numerous times for their favorite readings like this counting processes and survival analysis, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some malicious bugs inside their desktop computer. counting processes and survival analysis is available in our digital library an online access to it is set as public so you can get it instantly. Our books collection spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the counting processes and survival analysis is universally compatible with any devices to read.

331 citations

Journal ArticleDOI
TL;DR: A new rich annotated corpus of medical forum posts on patient-reported Adverse Drug Events (ADEs), which contains text that is largely written in colloquial language and often deviates from formal English grammar and punctuation rules.

217 citations


Cites background from "Text and Data Mining Techniques in ..."

  • ...A full review of these techniques can be found in [16]....

    [...]

Journal ArticleDOI
TL;DR: This Review provides a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting information demands of chemical information contained in scientific literature, patents, technical reports, or the web.
Abstract: Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the const...

197 citations

Journal Article
TL;DR: It can be estimated that 190,000 medication-related hospital admissions occur per year in Australia, with estimated costs of $660 million, and Medication incidents remain the second most common type of incident reported in Australian hospitals.
Abstract: Background This paper presents Part 1 of a two-part literature review examining medication safety in the Australian acute care setting. This review was undertaken for the Australian Commission on Safety and Quality in Health Care to update a previous national report on medication safety conducted in 2002. This first part of the review examines the extent and causes of medication incidents and adverse drug events in acute care. Methods A literature search was conducted to identify Australian studies, published from 2002 to 2008, on the extent and causes of medication incidents and adverse drug events in acute care. Results Studies published since 2002 continue to suggest approximately 2%-3% of Australian hospital admissions are medication-related. Results of incident reporting from hospitals show that incidents associated with medication remain the second most common type of incident after falls. Omission or overdose of medication is the most frequent type of medication incident reported. Studies conducted on prescribing of renally excreted medications suggest that there are high rates of prescribing errors in patients requiring monitoring and medication dose adjustment. Research published since 2002 provides a much stronger Australian research base about the factors contributing to medication errors. Team, task, environmental, individual and patient factors have all been found to contribute to error. Conclusions Medication-related hospital admissions remain a significant problem in the Australian healthcare system. It can be estimated that 190,000 medication-related hospital admissions occur per year in Australia, with estimated costs of $660 million. Medication incidents remain the second most common type of incident reported in Australian hospitals. A number of different systems factors contribute to the occurrence of medication errors in the Australian setting.

159 citations

References
More filters
Book
01 Jan 1988
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Abstract: From the Publisher: Probabilistic Reasoning in Intelligent Systems is a complete andaccessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty—and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition—in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

15,671 citations

Journal ArticleDOI
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Abstract: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points. This rule is independent of the underlying joint distribution on the sample points and their classifications, and hence the probability of error R of such a rule must be at least as great as the Bayes probability of error R^{\ast} --the minimum probability of error over all decision rules taking underlying probability structure into account. However, in a large sample analysis, we will show in the M -category case that R^{\ast} \leq R \leq R^{\ast}(2 --MR^{\ast}/(M-1)) , where these bounds are the tightest possible, for all suitably smooth underlying distributions. Thus for any number of categories, the probability of error of the nearest neighbor rule is bounded above by twice the Bayes probability of error. In this sense, it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.

12,243 citations

Journal ArticleDOI
TL;DR: It was shown that the ADR probability scale has consensual, content, and concurrent validity and may be applicable to postmarketing drug surveillance.
Abstract: The estimation of the probability that a drug caused an adverse clinical event is usually based on clinical judgment. Lack of a method for establishing causality generates large between-raters and within-raters variability in assessment. Using the conventional categories and definitions of definite, probable, possible, and doubtful adverse drug reactions (ADRs), the between-raters agreement of two physicians and four pharmacists who independently assessed 63 randomly selected alleged ADRs was 38% to 63%, kappa (k, a chance-corrected index of agreement) varied from 0.21 to 0.40, and the intraclass correlation coefficient of reliability (R[est]) was 0.49. Six (testing) and 22 wk (retesting) later the same observers independently reanalyzed the 63 cases by assigning a weighted score (ADR probability scale) to each of the components that must be considered in establishing causal associations between drug(s) and adverse events (e.g., temporal sequence). The cases were randomized to minimize the influence of learning. The event was assigned a probability category from the total score. The between-raters reliability (range: percent agreement = 83% to 92%; κ = 0.69 to 0.86; r = 0.91 to 0.95; R(est) = 0.92) and within-raters reliability (range: percent agreement = 80% to 97%; κ = 0.64 to 0.95; r = 0.91 to 0.98) improved (p < 0.001). The between-raters reliability was maintained on retesting (range: r = 0.84 to 0.94; R(est) = 0.87). The between-raters reliability of three attending physicians who independently assessed 28 other prospectively collected cases of alleged ADRs was very high (range: r = 0.76 to 0.87; R(est) = 0.80). It was also shown that the ADR probability scale has consensual, content, and concurrent validity. This systematic method offers a sensitive way to monitor ADRs and may be applicable to postmarketing drug surveillance. Clinical Pharmacology and Therapeutics (1981) 30, 239–245; doi:10.1038/clpt.1981.154

9,840 citations


"Text and Data Mining Techniques in ..." refers background in this paper

  • ...A good reasoning process tends to minimise the variability and inconsistency in assessment as shown decades ago by Naranjo et al. [1981]. Second, integrating data from various sources is essential for reaching reliable conclusions in the reasoning process....

    [...]