Combining HCI, Natural Language Processing, and Knowledge Discovery - Potential of IBM Content Analytics as an Assistive Technology in the Biomedical Field

@inproceedings{Holzinger2013CombiningHN,
  title={Combining HCI, Natural Language Processing, and Knowledge Discovery - Potential of IBM Content Analytics as an Assistive Technology in the Biomedical Field},
  author={Andreas Holzinger and Christof Stocker and Bernhard Ofner and Gottfried Prohaska and Alberto Brabenetz and Rainer Hofmann-Wellenhof},
  booktitle={CHI-KDD},
  year={2013}
}
Medical professionals are confronted with a flood of big data most of it containing unstructured information. Such unstructured information is the subset of information, where the information itself describes parts of what constitutes as significant within it, or in other words - structure and information are not completely separable. The best example for such unstructured information is text. For many years, text mining has been an essential area of medical informatics. Although text can… 

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References

SHOWING 1-10 OF 39 REFERENCES

Semantic Information in Medical Information Systems: Utilization of Text Mining Techniques to Analyze Medical Diagnoses

This paper proposes a calculation of significant co-occurrences of diseases and defined regions of the human body, in order to identify possible risks for health and designs and develops an application for analyzing expert comments on magnetic resonance images (MRI) diagnoses by applying a text mining method.

Text analytics for life science using the Unstructured Information Management Architecture

The value of text analysis in biomedical research, the development of the BioTeKS system, and applications which demonstrate its functions are described.

Quality-Based Knowledge Discovery from Medical Text on the Web

A selection of quality-oriented Web-based tools for analyzing biomedical literature are presented, and specifically discuss PolySearch, FACTA and Kleio and Pointwise Mutual Information (PMI), which is a measure to discover the strength of a relationship.

Text analysis and knowledge mining system

By applying the prototype system named TAKMI (Text Analysis and Knowledge Mining) to textual databases in PC help centers, the system can automatically detect product failures; determine issues that have led to rapid increases in the number of calls and their underlying reasons; and analyze help center productivity and changes in customers' behavior involving a particular product, without reading any of the text.

Status of text-mining techniques applied to biomedical text.

Disease-Disease Relationships for Rheumatic Diseases: Web-Based Biomedical Textmining an Knowledge Discovery to Assist Medical Decision Making

A web based text-mining tool is used to find disease names and their co-occurrence frequencies in MEDLINE articles for each disease and an evaluation on knowledge discovery of disease-disease relationships for rheumatic diseases is presented.

Supporting serendipity: Using ambient intelligence to augment user exploration for data mining and web browsing

  • R. Beale
  • Computer Science
    Int. J. Hum. Comput. Stud.
  • 2007

CASE‐BASED REASONING AND KNOWLEDGE DISCOVERY IN MEDICAL APPLICATIONS WITH TIME SERIES

The role and integration of knowledge discovery (KD) in case‐based reasoning (CBR) systems is discussed and it is shown that the approach is able to identify key sequences that would improve the classification ability and may spawn clinical research to explain the co‐occurrence between certain sequences and classes.

A Comparison of Different Retrieval Strategies Working on Medical Free Texts

This paper describes the evaluation of four different types of information retrieval strategies: keyword search, search performed by a medical domain expert, a semantic based information retrieval tool, and a purely statistical information retrieval method.

Naming notes: transitions from free text to structured entry.

A framework is set forth that connects over-arching questions concerning medical informatics systems development with the practical, cultural and conceptual issues involved in transitions from handwritten and other free text documentation to structured entry of medical records to build patient profiles.