Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics.

Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research.

[1]  A. Localio,et al.  Role of computerized physician order entry systems in facilitating medication errors. , 2005, JAMA.

[2]  Peter S White,et al.  Genomic annotation of the meningioma tumor suppressor locus on chromosome 1p34 , 2004, Oncogene.

[3]  Hsinchun Chen,et al.  A Cyber-archaeology Approach to Social Movement Research: Framework and Case Study , 2010, J. Comput. Mediat. Commun..

[4]  J. Keese,et al.  Pro-active approach to malware for healthcare information and imaging systems , 2005 .

[5]  Marc Berg,et al.  Viewpoint Paper: Some Unintended Consequences of Information Technology in Health Care: The Nature of Patient Care Information System-related Errors , 2003, J. Am. Medical Informatics Assoc..

[6]  Anand Kumar,et al.  Text mining and ontologies in biomedicine: Making sense of raw text , 2005, Briefings Bioinform..

[7]  Rhona MacDonald.  How animal passions became aroused , 2001, BMJ : British Medical Journal.

[8]  David Kotz,et al.  A threat taxonomy for mHealth privacy , 2011, 2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011).

[9]  Jeffrey P. Landry,et al.  A Threat Tree for Health Information Security and Privacy , 2011, AMCIS.

[10]  Ganthan Narayana Samy,et al.  Security threats categories in healthcare information systems , 2010, Health Informatics J..

[11]  A. Localio,et al.  Role of computerized physician order entry systems in facilitating medication errors. , 2005 .

[12]  Jimmy J. Lin,et al.  Semantic Clustering of Answers to Clinical Questions , 2007, AMIA.

[13]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

[14]  Munindar P. Singh,et al.  Service-Oriented Computing: Semantics, Processes, Agents , 2010 .

[15]  Hans-Peter Kriegel,et al.  Extraction of semantic biomedical relations from text using conditional random fields , 2008, BMC Bioinformatics.

[16]  Carole A. Goble,et al.  Ontology-based Knowledge Representation for Bioinformatics , 2000, Briefings Bioinform..

[17]  Matthias Lange,et al.  SEMEDA: ontology based semantic integration of biological databases , 2003, Bioinform..

[18]  Dejing Dou,et al.  OMIT: A Domain-Specific Knowledge Base for MicroRNA Target Prediction , 2011, Pharmaceutical Research.

[19]  Patrick Lambrix,et al.  Ontology-based integration for bioinformatics , 2005 .

[20]  Y. Han,et al.  Unexpected Increased Mortality After Implementation of a Commercially Sold Computerized Physician Order Entry System , 2005, Pediatrics.

[21]  Qi Tian,et al.  Text Mining in Radiology Reports , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[22]  W. Hersh,et al.  Health care information technology: progress and barriers. , 2004, JAMA.

[23]  Golan Yona,et al.  BIOZON: a system for unification, management and analysis of heterogeneous biological data , 2006, BMC Bioinformatics.

[24]  T. Kohno,et al.  Improving the security and privacy of implantable medical devices. , 2010, The New England journal of medicine.

[25]  Olivier Bodenreider,et al.  An Evaluation of Hybrid Methods for Matching Biomedical Terminologies: Mapping the Gene Ontology to the UMLS®$ , 2003, MIE.

[26]  L. Jean Camp,et al.  Threat analysis of online health information system , 2010, PETRA '10.

[27]  Kevin Fu.  Inside risksReducing risks of implantable medical devices , 2009, CACM.

[28]  H. Iseki,et al.  Computer Assisted Radiology and Surgery , 2010, International Journal of Computer Assisted Radiology and Surgery.

[29]  W J Curran,et al.  Privacy, confidentiality and other legal considerations in the establishment of a centralized health-data system. , 1969, The New England journal of medicine.

[30]  S. Henshaw,et al.  Providing controversial health care: abortion services since 1973. , 1993, Women's health issues : official publication of the Jacobs Institute of Women's Health.

[31]  Y. Han,et al.  Han YY, Carcillo JA, Venkataraman ST, Clark RS, Watson RS, Nguyen TC, Bayir H, Orr RA. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics , 2011 .

[32]  P. Kilbridge.  Computer crash--lessons from a system failure. , 2003, The New England journal of medicine.

[33]  M. Eric Johnson,et al.  Information security and privacy in healthcare: current state of research , 2010, Int. J. Internet Enterp. Manag..

[34]  G. Stoneburner,et al.  Risk Management Guide for Information Technology Systems: Recommendations of the National Institute of Standards and Technology , 2002 .