Authors:
Jesús Carreño-Bolufer
1
;
José Fabián Reyes Román
1
;
Sergio Pérez Andrés
1
;
Désirée Ramal Pons
2
;
Víctor Juárez Vidal
1
;
Adela Cañete Nieto
2
and
Óscar Pastor
1
Affiliations:
1
Valencian Research Institute for Artificial Intelligence (VRAIN), Universitat Politècnica de València, Valencia, Spain
;
2
Grupo de Investigación Clínica y Traslacional en Cáncer, Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain
Keyword(s):
ClinGenNBL, Conceptual Modeling, Neuroblastoma, Pediatric Oncology, Data Management, CMN.
Abstract:
Neuroblastoma is one of the leading causes of death in childhood oncology. Current treatments for these patients are general and not targeted, including radiotherapy, chemotherapy, and surgery. There is a need for more efficient methods. Precision Medicine (PM) can help to overcome this challenge. PM incorporates clinical, lifestyle, and genomic data, among others, into a standardized process to provide individualized treatment. However, a large amount of data is needed to achieve PM, and the heterogeneity present in the case of neuroblastoma poses a challenge for integration and, consequently, for knowledge generation. We need a solid domain definition that provides a foundation for experts to work on, which implies generating a conceptual model. Based on this model, any Information System (IS) can be developed. ISs play a vital role in managing clinical data efficiently. Much of the clinical data has been captured and managed over the years with inefficient tools such as spreadshee
ts. In this work, we first present the new Conceptual Model of Neuroblastoma (CMN), with a special focus on genomics, and second, ClinGenNBL, a conceptual model-based web application that implement the CMN with the goal of assisting clinicians in managing patients with neuroblastoma through a user-friendly interface.
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