Biomedical Term Extraction: NLP Techniques in Computational Medicine

Artificial Intelligence (AI) and its branch Natural Language Processing (NLP) in particular are main contributors to recent advances in classifying documentation and extracting information from assorted fields, Medicine being one that has gathered a lot of attention due to the amount of information generated in public professional journals and other means of communication within the medical profession. The typical information extraction task from technical texts is performed via an automatic term recognition extractor. Automatic Term Recognition (ATR) from technical texts is applied for the identification of key concepts for information retrieval and, secondarily, for machine translation. Term recognition depends on the subject domain and the lexical patterns of a given language, in our case, Spanish, Arabic and Japanese. In this article, we present the methods and techniques for creating a biomedical corpus of validated terms, with several tools for optimal exploitation of the information therewith contained in said corpus. This paper also shows how these techniques and tools have been used in a prototype

KACST Arabic Text Classification Project: Overview and Preliminary Results

Electronically formatted Arabic free-texts can be found in abundance these days on the World Wide Web, often linked to commercial enterprises and/or government organizations. Vast tracts of knowledge and relations lie hidden within these texts, knowledge that can be exploited once the correct intelligent tools have been identified and applied. For example, text mining may help with text classification and categorization. Text classification aims to automatically assign text to a predefined category based on identifiable linguistic features. Such a process has different useful applications including, but not restricted to, E-Mail spam detection, web pages content filtering, and automatic message routing. In this paper an overview of King Abdulaziz City for Science and Technology (KACST) Arabic Text Classification Project will be illustrated along with some preliminary results. This project will contribute to the better understanding and elaboration of Arabic text classification techniques

Boosting terminology extraction through crosslingual resources

Terminology Extraction is an important Natural Language Processing task with multiple applications in many areas. The task has been approached from different points of view using different techniques. Language and domain independent systems have been proposed as well. Our contribution in this paper focuses on the improvements on Terminology Extraction using crosslingual resources and specifically the Wikipedia and on the use of a variant of PageRank for scoring the candidate terms. // La extracción de terminología es una tarea de procesamiento de la lengua sumamente importante y aplicable en numerosas áreas. La tarea se ha abordado desde múltiples perspectivas y utilizando técnicas diversas. También se han propuesto sistemas independientes de la lengua y del dominio. La contribución de este artículo se centra en las mejoras que los sistemas de extracción de terminología pueden lograr utilizando recursos translingües, y concretamente la Wikipedia y en el uso de una variante de PageRank para valorar los candidatos a términoPeer ReviewedPostprint (published version

Query expansion using medical information extraction for improving information retrieval in French medical domain

Many users’ queries contain references to named entities, and this is particularly true in the medical field. Doctors express their information needs using medical entities as they are elements rich with information that helps to better target the relevant documents. At the same time, many resources have been recognized as a large container of medical entities and relationships between them such as clinical reports; which are medical texts written by doctors. In this paper, we present a query expansion method that uses medical entities and their semantic relations in the query context based on an external resource in OWL. The goal of this method is to evaluate the effectiveness of an information retrieval system to support doctors in accessing easily relevant information. Experiments on a collection of real clinical reports show that our approach reveals interesting improvements in precision, recall and MAP in medical information retrieval

Information Access in a Multilingual World: Transitioning from Research to Real-World Applications

Multilingual Information Access (MLIA) is at a turning point wherein substantial real-world applications are being introduced after fifteen years of research into cross-language information retrieval, question answering, statistical machine translation and named entity recognition. Previous workshops on this topic have focused on research and small- scale applications. The focus of this workshop was on technology transfer from research to applications and on what future research needs to be done which facilitates MLIA in an increasingly connected multilingual world

A medieval fallacy: the crystalline lens in the center of the eye.

ObjectiveTo determine whether, as most modern historians have written, ancient Greco-Roman authors believed the crystalline lens is positioned in the center of the eye.BackgroundHistorians have written that statements about cataract couching by Celsus, or perhaps Galen of Pergamon, suggested a centrally located lens. Celsus specifically wrote that a couching needle placed intermediate between the corneal limbus and the lateral canthus enters an empty space, presumed to represent the posterior chamber.MethodsAncient ophthalmic literature was analyzed to understand where these authors believed the crystalline lens was positioned. In order to estimate where Celsus proposed entering the eye during couching, we prospectively measured the distance from the temporal corneal limbus to the lateral canthus in 30 healthy adults.ResultsRufus of Ephesus and Galen wrote that the lens is anterior enough to contact the iris. Galen wrote that the lens equator joins other ocular structures at the corneoscleral junction. In 30 subjects, half the distance from the temporal corneal limbus to the lateral canthus was a mean of 4.5 mm (range: 3.3-5.3 mm). Descriptions of couching by Celsus and others are consistent with pars plana entry of the couching needle. Anterior angulation of the needle would permit contact of the needle with the lens.ConclusionAncient descriptions of anatomy and couching do not establish the microanatomic relationships of the ciliary region with any modern degree of accuracy. Nonetheless, ancient authors, such as Galen and Rufus, clearly understood that the lens is located anteriorly. There is little reason to believe that Celsus or other ancient authors held a variant understanding of the anatomy of a healthy eye. The notion of the central location of the lens seems to have arisen with Arabic authors in 9th century Mesopotamia, and lasted for over 7 centuries