PubMed · 10136129
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Three groups join IMSystem as quality partners.. https://pubmed.ncbi.nlm.nih.gov/10136129/
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The authors used the National Death Index and a World Wide Web Internet site that searches the Social Security Administration master files of deaths to determine the mortality status of 1,000 US subjects from the College Alumni Health Study. Subjects were classified as definitely dead, possibly dead, or presumed alive. Of 246 definite deaths pinpointed by the National Death Index, the World Wide Web identified 94.7% of them. Of 438 men presumed alive according to the National Death Index, the World Wide Web identified 97.5% of them. However, the World Wide Web was not useful for identifying deaths of women. This study demonstrated that the World Wide Web may provide an alternative, inexpensive method of determining the mortality status of subjects in relatively small epidemiologic studies.
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We review data mining techniques in molecular biology, specifically those that extract information from the scientific literature itself. As more of the biological literature is published electronically, there is an opportunity, and even a need, to automatically summarize the literature in a customized way, for example by associating keywords to a topic. These keywords can be extracted from relevant publications. The process of keyword extraction can be automated and optimized to keep literature pointers automatically up-to-date or to filter relevant information from the literature. To illustrate these points, OMIM (Online Mendelian Inheritance in Man), a database of human inherited diseases, was linked to the literature and keywords were derived that covered distinct aspects such as genetic information on the one hand and disease-specific protein and phenotypic information on the other. They were used to extract information that is helpful for keeping entries about disease up-to-date.