One of the most significant recent advances in health information systems has been the shift from paper to electronic documents. While research on automatic text and image processing has taken separate paths, there is a growing need for joint efforts, particularly for electronic health records and biomedical literature databases. This work aims at comparing text-based versus image-based access ...

Many corpora which are prime candidates for automatic error correction, such as the output of OCR software, and electronic texts incorporating markup tags, include information on which portions of the text are most likely to contain errors. This paper describes how the error markup tag is being incorporated in the spell-checking of an electronic version of Diderot's Encyclopddie, and evalua...

INTRODUCTION The UK government recommends that at least 75% of people aged under 64 with certain conditions receive an annual influenza vaccination. Primary care practices often fall short of this target and strategies to increase vaccine uptake are required. Text messaging reminders are already used in 30% of practices to remind patients about vaccination, but there has been no trial addressin...

ABSTRACT The Mathematical Discussion System (MDS) is a software system for supporting online discourse embedded in the context of an electronic educational text. Our goal was to create a new type of electronic resource that built upon the strengths of resources that are currently available to University students. Users of our system visit a specially formatted web page and are able to use our s...

Development of new text and graphical input devices is considered to be important part of humancomputer interaction by many researchers worldwide. The paper presents our experience with the text recognition methods that we have developed for a new designed electronic pen that produces signals corresponding to the movement of the pen on paper. Signals are described by a set of primitives and hid...

This paper presents a possible solution for the text inference problem—extracting information unstated in a text, but implied. Text inference is central to natural language applications such as information extraction and dissemination, text understanding, summarization, and translation. Our solution takes advantage of a semantic English dictionary available in electronic form that provides the ...

Employing a machine learning approach we predict, up to 24 hours prior, a diagnosis of severe sepsis. Strongly predictive models are possible that use only text reports from the Electronic Health Record (EHR), and omit structured numerical data. Unstructured text alone gives slightly better performance than structured data alone, and the combination further improves performance. We also discuss...

We propose a method for constructing a vector for a document image to represent its content to facilitate text retrieval. The method is based on an N-Gram algorithm for text similarity measure based on the frequency of occurrence of n-character strings appearing in the electronic text. Instead of using ASCII values, the present study investigates the use of character images to obtain the docume...

With the digitization of media, computers can be employed to help us with the process of classification, both by learning from our behavior to perform the task for us and by exposing new ways for us to think about our information. Given that most of our media comes in the form of electronic text, research in this area focuses on building automatic text classification systems. The standard repre...

This literature review included studies that use text-mining techniques in narrative documents stored in electronic patient records (EPRs) to investigate ADRs. We searched PubMed, Embase, Web of Science and International Pharmaceutical Abstracts without restrictions from origin until July 2011. We included empirically based studies on text mining of electronic patient records (EPRs) that focuse...