Data mining and CBR integrated methods in medicine: a review

@article{Pandey2010DataMA,
  title={Data mining and CBR integrated methods in medicine: a review},
  author={Babita Pandey and R. B. Mishra},
  journal={Int. J. Medical Eng. Informatics},
  year={2010},
  volume={2},
  pages={205-218}
}
Nowadays, a large number of data mining (DM) techniques are available for data analysis and prediction in medicine. Few literatures are available that provide a comprehensive view which give a guideline to use the DM techniques in different medical areas (domain). This review provides a comprehensive view of the state of the art of single DM and integrated case-based reasoning (CBR) and DM techniques in different medical domains such as: general medicine, nephrology, dermatology, cardiology… 
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References

SHOWING 1-10 OF 70 REFERENCES

Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis

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.

Predictive data mining in clinical medicine: Current issues and guidelines

Genetic programming for knowledge discovery in chest-pain diagnosis

GP has been demonstrated to be a really useful data mining tool, but future work should also include the application of the GP system proposed here to other data sets, to further validate the results reported in this article.

Temporal data mining for the quality assessment of hemodialysis services

Combining data mining and case-based reasoning for intelligent decision support for pathology ordering by general practitioners

Research and Application of Data Mining in Traditional Chinese Medical Clinic Diagnosis

The experiment with the data from the database of electronic patient cases shows that the Bayesian algorithm has good classification capability in traditional Chinese medical clinical diagnosis.

Rule induction and instance-based learning applied in medical diagnosis.

  • S. DžeroskiN. Lavrac
  • Computer Science, Medicine
    Technology and health care : official journal of the European Society for Engineering and Medicine
  • 1996
This paper presents the methodologies of rule induction and instance-based learning and their application to medical diagnosis, in particular, the problem of early diagnosis of rheumatic diseases and discusses the possibility to use existing expert knowledge to support the learning process and the utility of such knowledge.

Feature selection and classification model construction on type 2 diabetic patients' data

Data mining in predicting survival of kidney dialysis patients

A data mining approach is used to elicit knowledge about the interaction between multiple demographic and clinical variables and patient survival and two different data mining algorithms are employed for extracting knowledge in the form of decision rules.
...