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Semantic integration of cervical cancer data repositories to facilitate multicenter association studies: the ASSIST approach.

Agorastos T, Koutkias V, Falelakis M, Lekka I, Mikos T, Delopoulos A, Mitkas PA, Tantsis A, Weyers S, Coorevits P, Kaufmann AM, Kurzeja R, Maglaveras N - Cancer Inform (2009)

Bottom Line: The project aims to facilitate the research for cervical precancer and cancer through a system that virtually unifies multiple patient record repositories, physically located in different medical centers/hospitals, thus, increasing flexibility by allowing the formation of study groups "on demand" and by recycling patient records in new studies.The current paper presents the knowledge elicitation approach followed, towards the definition and representation of the disease's medical concepts and rules that constitute the basis for the ASSIST Cervical Cancer Ontology.The proposed approach constitutes a paradigm for semantic integration of heterogeneous clinical data that may be applicable to other biomedical application domains.

View Article: PubMed Central - PubMed

Affiliation: Department of Obstetrics and Gynecology, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Greece.

ABSTRACT
The current work addresses the unification of Electronic Health Records related to cervical cancer into a single medical knowledge source, in the context of the EU-funded ASSIST research project. The project aims to facilitate the research for cervical precancer and cancer through a system that virtually unifies multiple patient record repositories, physically located in different medical centers/hospitals, thus, increasing flexibility by allowing the formation of study groups "on demand" and by recycling patient records in new studies. To this end, ASSIST uses semantic technologies to translate all medical entities (such as patient examination results, history, habits, genetic profile) and represent them in a common form, encoded in the ASSIST Cervical Cancer Ontology. The current paper presents the knowledge elicitation approach followed, towards the definition and representation of the disease's medical concepts and rules that constitute the basis for the ASSIST Cervical Cancer Ontology. The proposed approach constitutes a paradigm for semantic integration of heterogeneous clinical data that may be applicable to other biomedical application domains.

No MeSH data available.


Related in: MedlinePlus

Viewing all available patients by Severity Index: On the left, all medical entities related to cervical cancer and pre cancer are displayed in a tree structure. The user can expand the tree items and select the type of information he/she wishes to use as search criteria. In this example, the user has selected Cervical Cancer Severity Code, meaning that all patients, for whom SI can be inferred, will be extracted. The preview of the query is shown on the top of the screen. On the right, the number of extracted records can be viewed both in table and graph format. For 32 patients, no diagnostic information was available; therefore, SI could not be inferred.
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f5-cin-08-31: Viewing all available patients by Severity Index: On the left, all medical entities related to cervical cancer and pre cancer are displayed in a tree structure. The user can expand the tree items and select the type of information he/she wishes to use as search criteria. In this example, the user has selected Cervical Cancer Severity Code, meaning that all patients, for whom SI can be inferred, will be extracted. The preview of the query is shown on the top of the screen. On the right, the number of extracted records can be viewed both in table and graph format. For 32 patients, no diagnostic information was available; therefore, SI could not be inferred.

Mentions: Suppose a researcher wishes to investigate whether there is an association between the MTHFR polymorphism and cervical precancerous lesions. While planning the study, he/she consults ASSIST to see, if there are shared data from patients with LCIN, HCIN and healthy patients for whom MTHFR genotype data are also available. The ASSIST User Interface offers the option to use the inferred ASSIST Cervical Cancer SI to express LCIN or HCIN, which is defined on the basis of the medical rules explained in section 2.4. Selecting a query to view all patients by inferred SI, the user can rapidly check the type of patients for whom data are shared through the ASSIST infrastructure (Fig. 5).


Semantic integration of cervical cancer data repositories to facilitate multicenter association studies: the ASSIST approach.

Agorastos T, Koutkias V, Falelakis M, Lekka I, Mikos T, Delopoulos A, Mitkas PA, Tantsis A, Weyers S, Coorevits P, Kaufmann AM, Kurzeja R, Maglaveras N - Cancer Inform (2009)

Viewing all available patients by Severity Index: On the left, all medical entities related to cervical cancer and pre cancer are displayed in a tree structure. The user can expand the tree items and select the type of information he/she wishes to use as search criteria. In this example, the user has selected Cervical Cancer Severity Code, meaning that all patients, for whom SI can be inferred, will be extracted. The preview of the query is shown on the top of the screen. On the right, the number of extracted records can be viewed both in table and graph format. For 32 patients, no diagnostic information was available; therefore, SI could not be inferred.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC2664695&req=5

f5-cin-08-31: Viewing all available patients by Severity Index: On the left, all medical entities related to cervical cancer and pre cancer are displayed in a tree structure. The user can expand the tree items and select the type of information he/she wishes to use as search criteria. In this example, the user has selected Cervical Cancer Severity Code, meaning that all patients, for whom SI can be inferred, will be extracted. The preview of the query is shown on the top of the screen. On the right, the number of extracted records can be viewed both in table and graph format. For 32 patients, no diagnostic information was available; therefore, SI could not be inferred.
Mentions: Suppose a researcher wishes to investigate whether there is an association between the MTHFR polymorphism and cervical precancerous lesions. While planning the study, he/she consults ASSIST to see, if there are shared data from patients with LCIN, HCIN and healthy patients for whom MTHFR genotype data are also available. The ASSIST User Interface offers the option to use the inferred ASSIST Cervical Cancer SI to express LCIN or HCIN, which is defined on the basis of the medical rules explained in section 2.4. Selecting a query to view all patients by inferred SI, the user can rapidly check the type of patients for whom data are shared through the ASSIST infrastructure (Fig. 5).

Bottom Line: The project aims to facilitate the research for cervical precancer and cancer through a system that virtually unifies multiple patient record repositories, physically located in different medical centers/hospitals, thus, increasing flexibility by allowing the formation of study groups "on demand" and by recycling patient records in new studies.The current paper presents the knowledge elicitation approach followed, towards the definition and representation of the disease's medical concepts and rules that constitute the basis for the ASSIST Cervical Cancer Ontology.The proposed approach constitutes a paradigm for semantic integration of heterogeneous clinical data that may be applicable to other biomedical application domains.

View Article: PubMed Central - PubMed

Affiliation: Department of Obstetrics and Gynecology, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Greece.

ABSTRACT
The current work addresses the unification of Electronic Health Records related to cervical cancer into a single medical knowledge source, in the context of the EU-funded ASSIST research project. The project aims to facilitate the research for cervical precancer and cancer through a system that virtually unifies multiple patient record repositories, physically located in different medical centers/hospitals, thus, increasing flexibility by allowing the formation of study groups "on demand" and by recycling patient records in new studies. To this end, ASSIST uses semantic technologies to translate all medical entities (such as patient examination results, history, habits, genetic profile) and represent them in a common form, encoded in the ASSIST Cervical Cancer Ontology. The current paper presents the knowledge elicitation approach followed, towards the definition and representation of the disease's medical concepts and rules that constitute the basis for the ASSIST Cervical Cancer Ontology. The proposed approach constitutes a paradigm for semantic integration of heterogeneous clinical data that may be applicable to other biomedical application domains.

No MeSH data available.


Related in: MedlinePlus