Natural Language Processing in Medicine: An Overview

Spyns, Peter

doi:10.1055/s-0038-1634681

Cited by 105 publications

(55 citation statements)

References 72 publications

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“…The main goal of this step is to use an approach to identify these interactions by using some Natural Language Processing (NLP) method [Spyns 1996] such as Shallow and Deep processing [Crysmann et al 2002] or Dependency parsing [Kubler et al 2009]. …”

Section: Relation Extraction Based On Regulatory Eventsmentioning

confidence: 99%

An approach towards the reconstruction of regulatory networks

Pereira

Costa

Mendes

2016

ComInG

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Abstract. Currently, one of the main issues addressed in the bioinformatics field is understanding the structure and behaviour of complex molecular interaction networks. Since most of the information available belongs to biomedical literature, a large part of this task entails selecting the relevant articles from a large body of papers. However, due to the rapidly increasing number of scientific papers, it is quite difficult to read all the papers that have been published about this subject. In order to accomplish this, this work is focused on developing methods for retrieving information from biological databases, gathering as much information as possible; to create an integrated repository, that is able to store and load this data and also to design a pipeline to allow the reconstruction of regulatory networks through using Biomedical Text Mining techniques.

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Section: Relation Extraction Based On Regulatory Eventsmentioning

confidence: 99%

An approach towards the reconstruction of regulatory networks

Pereira

Costa

Mendes

2016

ComInG

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“…Since the mid-90s, a vast amount of research has been conducted on applying natural language processing techniques in the area of medicine, biomedicine, and molecular biology [12,24,28,30,33]. It was recognized that natural language processing and text data mining is effective for information extraction.…”

Section: Motivation and Related Workmentioning

confidence: 99%

Towards applying text mining and natural language processing for biomedical ontology acquisition

Inniss

Lee²,

Light

et al. 2006

Proceedings of the 1st International Workshop on Text Mining in Bioinformatics

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The use of text mining and natural language processing can extend into the realm of knowledge acquisition and management for biomedical applications. In this paper, we describe how we implemented natural language processing and text mining techniques on the transcribed verbal descriptions from retinal experts of biomedical disease features. The feature-attribute pairs generated were then incorporated within a user interface for a collaborative ontology development tool. This tool, IDOCS, is being used in the biomedical domain to help retinal specialists reach a consensus on a common ontology for describing age-related macular degeneration (AMD). We compare the use of traditional text mining and natural language processing techniques with that of a retinal specialist's analysis and discuss how we might integrate these techniques for future biomedical ontology and user interface development.

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“…3) Guidance from Higher Order Knowledge: General NLP systems have traditionally followed a bottom-up approach mainly relying on part-of-speech preterminal tags. Medical NLP system typically includes improved word-level semantic tags [56]. Our current system uses a knowledge base of the primitive logical relations to both transform parser links to a conceptual representation and perform disambiguation.…”

Section: )mentioning

confidence: 99%

A Field Theoretical Approach to Medical Natural Language Processing

Taira

Bashyam

Kangarloo

2007

IEEE Trans. Inform. Technol. Biomed.

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Abstract-A parser for medical free text reports has been developed that is based on a chemistry/physics inspired "field theory" for word-word sentence-level dependencies. The transition from the linguistic world to the world of interacting particles with potential energies is guided by a psycholinguistics thought experiment related to the amount of "work" required to bring a reference word into an anchored configuration of words. Calibration experiments involving four and five grams were conducted. Data from these experiments were used as a knowledge source for estimating field conditions for words in sentences sampled from a corpus of medical reports. The result of the parser is a dependency tree that represents the global minimum energy state of the system of words for a given sentence. The system was trained and tested on a corpus of radiology reports. Preliminary performance, as quantified by link recall and precision statistics, is 84.9% and 89.9%, respectively. Index Terms-Knowledge representation, natural language processing (NLP), structured medical reporting.

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Natural Language Processing in Medicine: An Overview

Cited by 105 publications

References 72 publications

An approach towards the reconstruction of regulatory networks

An approach towards the reconstruction of regulatory networks

Towards applying text mining and natural language processing for biomedical ontology acquisition

A Field Theoretical Approach to Medical Natural Language Processing

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