Generator breast datamart—the novel breast cancer data discovery system for research and monitoring: Preliminary results and future perspectives

Fabio Marazzi, Luca Tagliaferri, Valeria Masiello, Francesca Moschella, Giuseppe Ferdinando Colloca, Barbara Corvari, Alejandro Martin Sanchez, Nikola Dino Capocchiano, Roberta Pastorino, Chiara Iacomini, Jacopo Lenkowicz, Carlotta Masciocchi, Stefano Patarnello, Gianluca Franceschini, Maria Antonietta Gambacorta, Riccardo Masetti, Vincenzo Valentini

Risultato della ricerca: Contributo in rivistaArticolo in rivista

2 Citazioni (Scopus)


Background: Artificial Intelligence (AI) is increasingly used for process management in daily life. In the medical field AI is becoming part of computerized systems to manage information and encourage the generation of evidence. Here we present the development of the application of AI to IT systems present in the hospital, for the creation of a DataMart for the management of clinical and research processes in the field of breast cancer. Materials and methods: A multidisciplinary team of radiation oncologists, epidemiologists, medical oncologists, breast surgeons, data scientists, and data management experts worked together to identify relevant data and sources located inside the hospital system. Combinations of open-source data science packages and industry solutions were used to design the target framework. To validate the DataMart directly on real-life cases, the working team defined tumoral pathology and clinical purposes of proof of concepts (PoCs). Results: Data were classified into “Not organized, not ‘ontologized’ data”, “Organized, not ‘ontologized’ data”, and “Organized and ‘ontologized’ data”. Archives of real-world data (RWD) identified were platform based on ontology, hospital data warehouse, PDF documents, and electronic reports. Data extraction was performed by direct connection with structured data or text-mining technology. Two PoCs were performed, by which waiting time interval for radiotherapy and performance index of breast unit were tested and resulted available. Conclusions: GENERATOR Breast DataMart was created for supporting breast cancer pathways of care. An AI-based process automatically extracts data from different sources and uses them for generating trend studies and clinical evidence. Further studies and more proof of concepts are needed to exploit all the potentials of this system.
Lingua originaleEnglish
pagine (da-a)1-10
Numero di pagine10
RivistaJournal of Personalized Medicine
Stato di pubblicazionePubblicato - 2021


  • Breast cancer
  • DataMart
  • Healthcare
  • Predictive model
  • Real world data


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