Obstacles and Misunderstandings Facing Medical Data Mining

  • Ashkan Sami
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4093)


Medical Data Mining is a very active and challenging research area in Data Mining community. However researchers entering Medical Data Mining should be aware that in core clinical, dentistry and nursing, data mining is not welcomed as much as we believe and publication of results in these journals based on Data Mining algorithms is not easily possible. In this paper, in addition to presenting one of our “successful” KDD projects in Urology that did not get to anywhere, we back up our belief based on designed searches on PubMed and review literature based on these searches. Our findings suggest that few Data Mining algorithms made their ways into core clinical journals. The paper concludes by reasons we have collected through our experiences.


Data Mining Data Mining Algorithm Human African Trypanosomiasis Bayesian Neural Network Damage Control Laparotomy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ashkan Sami
    • 1
  1. 1.Department of Computer Science and EngineeringShiraz UniversityShirazIran

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