A semantic interoperability approach to support integration of gene expression and clinical data in breast cancer

Alonso-Calvo, Raúl; Paraiso-Medina, Sergio; Pérez-Rey, David; Alonso-Oset, E.; Stiphout, Ruud van; Yu, Sheng; Taylor, Marian; Buffa, Francesca M.; Fernández-Lozano, Carlos; Maojo, Víctor

doi:10.1016/j.compbiomed.2017.06.005

Cited by 16 publications

(12 citation statements)

References 28 publications

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“…The main reason for the widespread of SOA paradigm is that it proposes a highly feasible strategy to easily promote the integration and alignment of new and existing solutions in a cohesive architecture, with minimal impact for service consumers, resulting in a highly reduced economic cost [19][20][21]. For these reasons, this approach was successfully adopted in distributed healthcare architectures [22,23]. Compliance with these standards guarantees a wide reuse of the efforts made to produce the suggested architecture and its stability of use over the years.…”

Section: Methodsmentioning

confidence: 99%

Towards an Electronic Medical Record for Precision Oncology: Information and Knowledge Management

Maggi

Ruggiero

2018

2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)

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Paper medical records are still widely used in Italian hospitals and their use contributes to the reduced efficiency of the clinical process. Appropriate standards can improve the functioning of Health Information Technology and contribute to the improvement of quality and patient safety. A global architecture scheme was implemented by harmonising health services as proposed by HL7 to achieve interoperability between distributed and heterogeneous applications and devices belonging to independent organisations. A client application was developed that led to the improvement of the quantity and quality of information that may be relevant for the treatment of patients suffering from colorectal cancer. A tailoring application was designed and developed to meet the needs of medical personnel, especially as regards the management of visits, and the creation of a clinical diary in compliance with the standards currently in use. This work is the basis for an integration of medical records and genomic data that can lead to an improvement in cancer prevention, diagnosis, prognosis and treatment (precision oncology).

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Section: Methodsmentioning

confidence: 99%

Towards an Electronic Medical Record for Precision Oncology: Information and Knowledge Management

Maggi

Ruggiero

2018

2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)

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“…Even in studies on building frameworks or platforms to support or automate the data integration process (especially those related to creating integrated dataset to support cancer research), they often ignored the need for documenting the integration steps to guarantee the transparency and reproducibility of their approaches. For example, semantic data integration approach —connecting variables across different databases at the semantic level through mapping them to standardized concepts in a global schema (e.g., often time a global ontology) — has been proposed in data integration studies in recent years to support generating integrated datasets for cancer research [ 23 – 25 ]. However, none of these studies mentioned the need for standardizing and documenting their integration steps, for example, most of them did not even discuss the rationale for selecting the specific data sources to integrate.…”

Section: Introductionmentioning

confidence: 99%

An ontology-based documentation of data discovery and integration process in cancer outcomes research

Zhang

Guo

Prosperi

et al. 2020

BMC Med Inform Decis Mak

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Background To reduce cancer mortality and improve cancer outcomes, it is critical to understand the various cancer risk factors (RFs) across different domains (e.g., genetic, environmental, and behavioral risk factors) and levels (e.g., individual, interpersonal, and community levels). However, prior research on RFs of cancer outcomes, has primarily focused on individual level RFs due to the lack of integrated datasets that contain multi-level, multi-domain RFs. Further, the lack of a consensus and proper guidance on systematically identify RFs also increase the difficulty of RF selection from heterogenous data sources in a multi-level integrative data analysis (mIDA) study. More importantly, as mIDA studies require integrating heterogenous data sources, the data integration processes in the limited number of existing mIDA studies are inconsistently performed and poorly documented, and thus threatening transparency and reproducibility. Methods Informed by the National Institute on Minority Health and Health Disparities (NIMHD) research framework, we (1) reviewed existing reporting guidelines from the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) network and (2) developed a theory-driven reporting guideline to guide the RF variable selection, data source selection, and data integration process. Then, we developed an ontology to standardize the documentation of the RF selection and data integration process in mIDA studies. Results We summarized the review results and created a reporting guideline—ATTEST—for reporting the variable selection and data source selection and integration process. We provided an ATTEST check list to help researchers to annotate and clearly document each step of their mIDA studies to ensure the transparency and reproducibility. We used the ATTEST to report two mIDA case studies and further transformed annotation results into sematic triples, so that the relationships among variables, data sources and integration processes are explicitly standardized and modeled using the classes and properties from OD-ATTEST. Conclusion Our ontology-based reporting guideline solves some key challenges in current mIDA studies for cancer outcomes research, through providing (1) a theory-driven guidance for multi-level and multi-domain RF variable and data source selection; and (2) a standardized documentation of the data selection and integration processes powered by an ontology, thus a way to enable sharing of mIDA study reports among researchers.

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“…SOA is widely used for real time implementation in large distributed systems, mostly because it supports the easy integration of new software within the existing one, reducing the impact on service users and cost [17][18][19][20]. Moreover, the SOA paradigm has been successfully implemented in the design of several distributed healthcare systems [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

A Modular Multipurpose, Parameter Centered Electronic Health Record Architecture

Maggi¹,

Magnoni²,

Ruggiero³

et al. 2019

Adv. sci. technol. eng. syst. j.

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Health Information Technology is playing a key role in healthcare. Specifically, the use of electronic health records has been found to bring about most significant improvements in healthcare quality, mainly as relates to patient management, healthcare delivery and research support. Health record systems adoption has been promoted in many countries to support efficient, high quality integrated healthcare. The objective of this work is the implementation of an Electronic Health Record system based on a relational database. The system architecture is modular and based on the concentration of specific pathology related parameters in one module, therefore the system can be easily applied to different pathologies. Several examples of its application are described. It is intended to extend the system integrating genomic data.

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A semantic interoperability approach to support integration of gene expression and clinical data in breast cancer

Abstract: The SIL has been adopted in national and international research initiatives, such as the EURECA-EU research project and the CIMED collaborative Spanish project, where the proposed solution has been applied and evaluated by clinical experts focused on clinico-genomic studies.

Cited by 16 publications

References 28 publications

Towards an Electronic Medical Record for Precision Oncology: Information and Knowledge Management

Towards an Electronic Medical Record for Precision Oncology: Information and Knowledge Management

An ontology-based documentation of data discovery and integration process in cancer outcomes research

A Modular Multipurpose, Parameter Centered Electronic Health Record Architecture

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