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

Zhuang, Zoe Yan; Чурилов, Леонид; Burstein, Frada; Sikaris, Ken

doi:10.1016/j.ejor.2007.11.003

Cited by 85 publications

(30 citation statements)

References 22 publications

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“…Recently, CBR has attracted considerable research interest to support the selection and recommendation of treatment. Zhuang et al [36] combined data mining and CBR methodologies to provide GPs with intelligent decision support for pathology tests ordering. They guarantee that the integrated system can enhance the testing ordering in terms of its evidence base, situational relevance, flexibility and interactivity.…”

Section: Case-based Reasoning In Medical Prescriptionmentioning

confidence: 99%

“…Therefore, we apply the CBR approach proposed by [36] to specifically retrieve previously experienced cases with information on concrete problem situations and their solutions. As each retrieved case represents a particular patient's medical history on the basis of a physician's specific knowledge of the prescription practices, the solution obtained in the CBR process relates a specific patient to the physician (i.e.…”

Section: Concept Of 'Micro-view' and 'Macro-view'mentioning

confidence: 99%

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A hybrid knowledge-based approach to supporting the medical prescription for general practitioners: Real case in a Hong Kong medical center

Ting

Kwok

Tsang

et al. 2011

Knowledge-Based Systems

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ObjectiveWith the increased complexity and uncertainty in drug information, issuing medical prescriptions has become a vexing issue. As many as 240,000 medicines are available on the market, so this paper proposes a novel approach to the issuing of medical prescriptions. The proposed process will provide general practitioners (GPs) with medication advice and suggest a range of medicines for specific medical conditions by taking into consideration the collective pattern as well as the individual preferences of physicians' prescription decisions. Methods and MaterialA hybrid approach is described that uses a combination of case-based reasoning (CBR) and Bayesian reasoning. In the CBR process, all the previous knowledge retrieved via similarity measures is made available for the reference of physicians as to what medicines have been prescribed (to a particular patient) in the past. After obtaining the results from CBR, Bayesian reasoning is then applied to model the prescription experience of all physicians within the organization. By comparing the two sets of results, more refined recommendations on a range of medicines are suggested along with the ranking for each recommendation. ResultsTo validate the proposed approach, a Hong Kong medical center was selected as a testing site. Through application of the hybrid approach in the medical center for a period of one month, the results demonstrated that the approach produced satisfactory performance in terms of user satisfaction, ease of use, flexibility and effectiveness. In addition, the proposed approach yields better results and a faster learning rate than This is the Pre-Published Version. 2 when either CBR or Bayesian reasoning are applied alone. ConclusionEven with the help of a decision support system, the current approach to anticipating what drugs are to be prescribed is not flexible enough to cater for individual preferences of GPs, and provides little support for managing complex and dynamic changes in drug information. Therefore, with the increase in the amount of information about drugs, it is extremely difficult for physicians to write a good prescription. By integrating CBR and Bayesian reasoning, the general practitioners' prescription practices can be retrieved and compared with the collective prescription experience as modeled by probabilistic reasoning. As a result, physicians can select the drugs which are supported by informed evidential decisions. That is, they can take into consideration the pattern of decisions made by other physicians in similar cases.

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Section: Case-based Reasoning In Medical Prescriptionmentioning

confidence: 99%

Section: Concept Of 'Micro-view' and 'Macro-view'mentioning

confidence: 99%

A hybrid knowledge-based approach to supporting the medical prescription for general practitioners: Real case in a Hong Kong medical center

Ting

Kwok

Tsang

et al. 2011

Knowledge-Based Systems

View full text Add to dashboard Cite

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“…In this framework, FW is used to estimate the optimal weights of the original features of cases [27], [28] , and FS is employed when choosing relevant features of cases [20], [22], or their aggregation is used to leverage their usefulness [19]. Second, to merge data clustering with KNN, where the structure of clustered cases is leveraged to lead to more relevant cases [29], [30]. For case retrieval, the similarity between a target problem and each case is combined with the relevance of the clustered group containing the case considered [31].…”

Section: Data Mining and Cbrmentioning

confidence: 99%

A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association

Aljuboori

Meziane

Parsons

2016

Machine Learning and Data Mining in Pattern Recognition

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“…A system to extract association rules from health examination data has been proposed, after that a case-based reasoning model is used to support the continual disease analysis and management [9]. A different rule mining method with case-based reasoning has been applied recently [10]. Medical data warehouses have been constructed [11] as an extension to the normal medical databases.…”

Section: Related Workmentioning

confidence: 99%

Mining Medical Databases Using Graph based Association Rules

AlZoubi¹

2013

IJMLC

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Abstract-Medical databases have accumulated huge amounts of information about patients and their medical conditions. Relationships and patterns within these data can provide new medical knowledge. Sorry to say that few methodologies have been developed and applied to discover this hidden knowledge. In this paper, the graph bases association rules mining (data mining is the main part of Knowledge Discovery in Databases) is used to search for relationships in a large medical database. The data that was collected on 6549 obstetrical patients were evaluated for factors potentially contributing to preterm birth using exploratory factor analysis. This paper describes the processes involved in mining a medical database including data warehousing, data query and cleaning, and data analysis.Index Term-Graph, medical database, rule mining.

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

Cited by 85 publications

References 22 publications

A hybrid knowledge-based approach to supporting the medical prescription for general practitioners: Real case in a Hong Kong medical center

A hybrid knowledge-based approach to supporting the medical prescription for general practitioners: Real case in a Hong Kong medical center

A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association

Mining Medical Databases Using Graph based Association Rules

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