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Berti A. & Carloni G., et al. "Data Models for an Imaging Bio-bank for Colorectal, Prostate and Gastric Cancer: the NAVIGATOR Project" in IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI) 2022

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Titolo convegno/congresso: IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 27-30/09/2022, Ioannina (Greece).

AutoriAndrea Berti (1,2,*), Gianluca Carloni (1,2,*), Sara Colantonio (1), M. Antonietta Pascali (1), Paolo Manghi (1), Pasquale Pagano (1), Rossana Buongiorno (1,2), Eva Pachetti (1,2), Claudia Caudai (1), Domenico di Gangi (1), Emanuele Carlini (1), Zeno Falaschi (3), Esther Ciarrocchi (3), Emanuele Neri (3), Elena Bertelli (4), Vittorio Miele (4), Roberto Carpi (5), Giulio Bagnacci (6), Nunzia di Meglio (6), M. Antonietta Mazzei (6), Andrea Barucci (7).

Affiliazioni: (1): Institute of Information Science and Technologies - ISTI-CNR, Pisa, Italy (2): Department of Information Engineering, University of Pisa, Pisa, Italy (3): Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, Pisa, Italy (4): Azienda Ospedaliera Universitaria Careggi, Florence, Italy (5): Azienda USL Toscana Centro, Florence, Italy (6): Azienda Ospedaliera Universitaria Senese, Siena, Italy (7): Institute of Applied Physics - IFAC-CNR, Florence, Italy. *: These authors share the first authorship.

Abstract:

Researchers nowadays may take advantage of broad collections of medical data to develop personalized medicine solutions. Imaging bio-banks play a fundamental role, in this regard, by serving as organized repositories of medical images associated with imaging biomarkers. In this context, the NAVIGATOR Project aims to advance colorectal, prostate, and gastric oncology translational research by leveraging quantitative imaging and multi-omics analyses. As Project's core, an imaging bio-bank is being designed and implemented in a web-accessible Virtual Research Environment (VRE). The VRE serves to extract the imaging biomarkers and further process them within prediction algorithms. In our work, we present the realization of the data models for the three cancer use-cases of the Project. First, we carried out an extensive requirements analysis to fulfill the necessities of the clinical partners involved in the Project. Then, we designed three separate data models utilizing entity-relationship diagrams. We found diagrams' modeling for colorectal and prostate cancers to be more straightforward, while gastric cancer required a higher level of complexity. Future developments of this work would include designing a common data model following the Observational Medical Outcomes Partnership Standards. Indeed, a common data model would standardize the logical infrastructure of data models and make the bio-bank easily interoperable with other bio-banks.

Rivista: Conference proceedings (IEEE Eng. Med. Biol. Soc., Conf.), Attiva dal 2004, Editore: IEEE Service Center, - Piscataway, NJ
Paese di pubblicazione: Stati Uniti d'America, Lingua: inglese, ISSN: 1557-170X.

DOI https://doi.org/10.1109/BHI56158.2022.9926910