| 1. |
- Ridderstolpe, Lisa, et al.
(författare)
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Canonical correlation analysis of risk factors and clinical outcomes in cardiac surgery
- 2005
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Ingår i: Journal of medical systems. - : Springer. - 0148-5598 .- 1573-689X. ; 29:4, s. 357-377
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Tidskriftsartikel (refereegranskat)abstract
- Assessment of the association between risk factors and outcomes in cardiac surgery is a complex problem. The aim of this study was to explore the relationship between possible risk factors and several clinical outcomes in cardiac surgery by using canonical correlation analysis (CCA). This retrospective study of 2605 consecutive adult patients who underwent cardiac surgery, evaluated 74 potential risk factors and up to 12 outcomes by canonical correlation analysis. For three serious outcomes, sternal wound complications/mediastinitis, cerebral complications, and perioperative myocardial infarctions, CCA was preceded by univariate analyses and backward stepwise multivariate logistic regression analyses. The CCA suggests that the major risk factors for complications in these models are intraoperative and postoperative risk factors. The power of risk prediction models developed with multivariate regression analysis can be enhanced by application of canonical correlation analysis, thereby offering new ways of analyzing and interpreting sets of potential risk factors in relation to sets of clinical outcomes.
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| 4. |
- Razavi, Amir Reza, 1973-, et al.
(författare)
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An approach for generating fuzzy rules from decision trees
- 2006
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Ingår i: Ubiquity. - : IOS Press. - 9781586036478 ; , s. 581-586
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Konferensbidrag (refereegranskat)abstract
- Identifying high-risk breast cancer patients is vital both for clinicians and for patients. Some variables for identifying these patients such as tumor size are good candidates for fuzzification. In this study, Decision Tree Induction (DTI) has been applied to 3949 female breast cancer patients and crisp If-Then rules has been acquired from the resulting tree. After assigning membership functions for each variable in the crisp rules, they were converted into fuzzy rules and a mathematical model was constructed. One hundred randomly selected cases were examined by this model and compared with crisp rules predictions. The outcomes were examined by the area under the ROC curve (AUC). No significant difference was noticed between these two approaches for prediction of recurrence of breast cancer. By soft discretization of variables according to resulting rules from DTI, a predictive model, which is both more robust to noise and more comprehensible for clinicians, can be built.
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| 5. |
- Razavi, Amir Reza, 1973-, et al.
(författare)
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Canonical correlation analysis for data reduction in data mining applied to predictive models for breast cancer recurrence
- 2005
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Ingår i: The XIXth International Congress of the European Federation for Medical Informatics,2005. - Amsterdam : IOSPress. ; , s. 175-180
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Konferensbidrag (refereegranskat)abstract
- Data mining methods can be used for extracting specific medical knowledge such as important predictors for recurrence of breast cancer in pertinent data material. However, when there is a huge quantity of variables in the data material it is first necessary to identify and select important variables. In this study we present a preprocessing method for selecting important variables in a dataset prior to building a predictive model. In the dataset, data from 5787 female patients were, analysed. To cover more predictors and obtain a better assessment of the outcomes, data were retrieved from three different registers: the regional breast cancer, tumour markers, and cause of death registers. After retrieving information about selected predictors and outcomes from the different registers, the raw data were cleaned by running different logical rules. Thereafter, domain experts selected predictors assumed to be important regarding recurrence of breast cancer. After that, Canonical Correlation Analysis (CCA) was applied as a dimension reduction technique to preserve the character of the original data. Artificial Neural Network (ANN) was applied to the resulting dataset for two different analyses with the same settings. Performance of the predictive models was confirmed by ten-fold cross validation. The results showed an increase in the accuracy of the prediction and reduction of the mean absolute error.
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| 6. |
- Razavi, Amir Reza, 1973-, et al.
(författare)
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Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer
- 2007
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Ingår i: MEDINFO 2007: PROCEEDINGS OF THE 12TH WORLD CONGRESS ON HEALTH (MEDICAL) INFORMATICS, PTS 1 AND 2. - : IOS Press. - 9781586037741 ; , s. 591-595
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Konferensbidrag (refereegranskat)abstract
- Postmastectomy radiotherapy (PAMT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of noncompliance between the actual treatment and the PMRT guideline.Data from breast cancer patients admitted to Linkoping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline.Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.
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| 7. |
- Nilsson, Gunnar H., et al.
(författare)
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Patients, general practitioners, diseases and health problems in urban general practice: a cross-sectional study on electronic patient records
- 2008
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Ingår i: Primary Health Care Research & Development. - : Cambridge University Press (CUP). - 1463-4236 .- 1477-1128. ; 9:02, s. 119-125
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Tidskriftsartikel (refereegranskat)abstract
- Background: Statistics from primary health care in Sweden, as well as from other Nordic countries, have been sparse. The electronic patient records (EPR) will be an increasingly important source of clinical information. The aim of this study was to investigate types of encounters, managed diseases and health problems, and characteristics of patients and general practitioners (GPs) in everyday general practice using EPR. Methods: A multi-centre, cross-sectional database study of EPR in primary health care in Stockholm, Sweden. Twenty-six randomly selected GPs with 20 randomly selected encounters each. Main outcome measures were the number and distribution of diseases and health problems, age and gender of patients and GPs, and type of encounter. Results: The mean age of the patients was 51.2 years, 30.2% were aged 75 years or older, and 57.5% were women. The mean number of managed problems per encounter was 1.4. The most common specific diagnoses were essential hypertension (9.3% of the encounters) and acute upper respiratory infections (8.8%). Older patients had more health problems in each encounter (P = 0.000001). GPs differed regarding the characteristics of their patients, including sex, age and number of health problems managed at each encounter. The patients of different GPs differed regarding sex, age and number of health problems managed. Female and male patients had different diagnostic panoramas and they had a tendency to encounter a GP of the same sex (odds ratio 1.5, P = 0.053). Conclusions: We found that two diagnoses (essential hypertension and acute upper respiratory infections), four diagnostic groups, women and the elderly are predominant. Female and male patients have different diagnostic panoramas and they have a tendency to encounter a GP of the same sex. GPs differ regarding the characteristics of their patients, including sex, age and number of health problems managed at each encounter.
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| 8. |
- Nyström, Mikael, 1977-, et al.
(författare)
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Creating a medical dictionary using word alignment : The influence of sources and resources
- 2007
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Ingår i: BMC Medical Informatics and Decision Making. - : Springer Science and Business Media LLC. - 1472-6947. ; 7:37
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Tidskriftsartikel (refereegranskat)abstract
- Background. Automatic word alignment of parallel texts with the same content in different languages is among other things used to generate dictionaries for new translations. The quality of the generated word alignment depends on the quality of the input resources. In this paper we report on automatic word alignment of the English and Swedish versions of the medical terminology systems ICD-10, ICF, NCSP, KSH97-P and parts of MeSH and how the terminology systems and type of resources influence the quality. Methods. We automatically word aligned the terminology systems using static resources, like dictionaries, statistical resources, like statistically derived dictionaries, and training resources, which were generated from manual word alignment. We varied which part of the terminology systems that we used to generate the resources, which parts that we word aligned and which types of resources we used in the alignment process to explore the influence the different terminology systems and resources have on the recall and precision. After the analysis, we used the best configuration of the automatic word alignment for generation of candidate term pairs. We then manually verified the candidate term pairs and included the correct pairs in an English-Swedish dictionary. Results. The results indicate that more resources and resource types give better results but the size of the parts used to generate the resources only partly affects the quality. The most generally useful resources were generated from ICD-10 and resources generated from MeSH were not as general as other resources. Systematic inter-language differences in the structure of the terminology system rubrics make the rubrics harder to align. Manually created training resources give nearly as good results as a union of static resources, statistical resources and training resources and noticeably better results than a union of static resources and statistical resources. The verified English-Swedish dictionary contains 24,000 term pairs in base forms. Conclusion. More resources give better results in the automatic word alignment, but some resources only give small improvements. The most important type of resource is training and the most general resources were generated from ICD-10. © 2007 Nyström et al, licensee BioMed Central Ltd.
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| 9. |
- Nyström, Mikael, 1977-, et al.
(författare)
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Creating a medical English-Swedish dictionary using interactive word alignment
- 2006
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Ingår i: BMC Medical Informatics and Decision Making. - : Springer Science and Business Media LLC. - 1472-6947. ; 6:35
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Tidskriftsartikel (refereegranskat)abstract
- Background: This paper reports on a parallel collection of rubrics from the medical terminology systems ICD-10, ICF, MeSH, NCSP and KSH97-P and its use for semi-automatic creation of an English-Swedish dictionary of medical terminology. The methods presented are relevant for many other West European language pairs than English-Swedish. Methods: The medical terminology systems were collected in electronic format in both English and Swedish and the rubrics were extracted in parallel language pairs. Initially, interactive word alignment was used to create training data from a sample. Then the training data were utilised in automatic word alignment in order to generate candidate term pairs. The last step was manual verification of the term pair candidates. Results: A dictionary of 31,000 verified entries has been created in less than three man weeks, thus with considerably less time and effort needed compared to a manual approach, and without compromising quality. As a side effect of our work we found 40 different translation problems in the terminology systems and these results indicate the power of the method for finding inconsistencies in terminology translations. We also report on some factors that may contribute to making the process of dictionary creation with similar tools even more expedient. Finally, the contribution is discussed in relation to other ongoing efforts in constructing medical lexicons for non-English languages. Conclusion: In three man weeks we were able to produce a medical English-Swedish dictionary consisting of 31,000 entries and also found hidden translation errors in the utilized medical terminology systems. © 2006 Nyström et al, licensee BioMed Central Ltd.
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| 12. |
- Sundvall, Erik, 1973-, et al.
(författare)
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Graphical Overview and Navigation of Electronic Health Records in a prototyping environment using Google Earth and openEHR Archetypes
- 2007
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Ingår i: MEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics – Building Sustainable Health Systems. - : IOS Press. - 9781586037741 ; 129:Pt 2, s. 1043-7
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Konferensbidrag (refereegranskat)abstract
- This paper describes selected earlier approaches to graphically relating events to each other and to time; some new combinations are also suggested. These are then combined into a unified prototyping environment for visualization and navigation of electronic health records. Google Earth (GE) is used for handling display and interaction of clinical information stored using openEHR data structures and ‘archetypes’. The strength of the approach comes from GE's sophisticated handling of detail levels, from coarse overviews to fine-grained details that has been combined with linear, polar and region-based views of clinical events related to time. The system should be easy to learn since all the visualization styles can use the same navigation.The structured and multifaceted approach to handling time that is possible with archetyped openEHR data lends itself well to visualizing and integration with openEHR components is provided in the environment.
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| 13. |
- Sundvall, Erik, 1973-, et al.
(författare)
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Integration of Tools for Binding Archetypes to SNOMED CT
- 2008
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Ingår i: BMC Medical Informatics and Decision Making. - : Springer. - 1472-6947. ; 8:S7
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.MethodsLexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.ResultsAn integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.ConclusionFinding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.BackgroundThe Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.MethodsLexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.ResultsAn integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.ConclusionFinding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.
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| 14. |
- Sundvall, Erik, 1973-, et al.
(författare)
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Interactive Visualization and Navigation of Complex Terminology Systems, Exemplified by SNOMED CT
- 2006
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Ingår i: Ubiquity. - : IOS Press. - 9781586036478 ; , s. 851-856
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Konferensbidrag (refereegranskat)abstract
- Free-text queries are natural entries into the exploration of complex terminology systems. The way search results are presented has impact on the users ability to grasp the overall structure of the system. Complex hierarchies like the one used in SNOMED CT, where nodes have multiple parents (IS-A) and several other relationship types, makes visualization challenging. This paper presents a prototype, Term Viz, applying well known methods like "focus+context" and self-organizing layouts from the fields of Information Visualization and Graph Drawing to terminologies like SNOMED CT and ICD-10. The user can simultaneously focus on several nodes in the terminologies and then use interactive animated graph navigation and semantic zooming to further explore the terminology systems without loosing context. The prototype, based on Open Source Java components, demonstrates how a number of Information Visualisation methods can aid the exploration of medical terminologies with millions of elements and can serve as a base for further development.
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