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GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives
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...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7911086/ https://www.ncbi.nlm.nih.gov/pubmed/33498985 http://dx.doi.org/10.3390/jpm11020065 |
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author | Marazzi, Fabio Tagliaferri, Luca Masiello, Valeria Moschella, Francesca Colloca, Giuseppe Ferdinando Corvari, Barbara Sanchez, Alejandro Martin Capocchiano, Nikola Dino Pastorino, Roberta Iacomini, Chiara Lenkowicz, Jacopo Masciocchi, Carlotta Patarnello, Stefano Franceschini, Gianluca Gambacorta, Maria Antonietta Masetti, Riccardo Valentini, Vincenzo |
author_facet | Marazzi, Fabio Tagliaferri, Luca Masiello, Valeria Moschella, Francesca Colloca, Giuseppe Ferdinando Corvari, Barbara Sanchez, Alejandro Martin Capocchiano, Nikola Dino Pastorino, Roberta Iacomini, Chiara Lenkowicz, Jacopo Masciocchi, Carlotta Patarnello, Stefano Franceschini, Gianluca Gambacorta, Maria Antonietta Masetti, Riccardo Valentini, Vincenzo |
author_sort | Marazzi, Fabio |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7911086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79110862021-02-28 GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives Marazzi, Fabio Tagliaferri, Luca Masiello, Valeria Moschella, Francesca Colloca, Giuseppe Ferdinando Corvari, Barbara Sanchez, Alejandro Martin Capocchiano, Nikola Dino Pastorino, Roberta Iacomini, Chiara Lenkowicz, Jacopo Masciocchi, Carlotta Patarnello, Stefano Franceschini, Gianluca Gambacorta, Maria Antonietta Masetti, Riccardo Valentini, Vincenzo J Pers Med Article 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. MDPI 2021-01-22 /pmc/articles/PMC7911086/ /pubmed/33498985 http://dx.doi.org/10.3390/jpm11020065 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Marazzi, Fabio Tagliaferri, Luca Masiello, Valeria Moschella, Francesca Colloca, Giuseppe Ferdinando Corvari, Barbara Sanchez, Alejandro Martin Capocchiano, Nikola Dino Pastorino, Roberta Iacomini, Chiara Lenkowicz, Jacopo Masciocchi, Carlotta Patarnello, Stefano Franceschini, Gianluca Gambacorta, Maria Antonietta Masetti, Riccardo Valentini, Vincenzo GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives |
title | GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives |
title_full | GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives |
title_fullStr | GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives |
title_full_unstemmed | GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives |
title_short | GENERATOR Breast DataMart—The Novel Breast Cancer Data Discovery System for Research and Monitoring: Preliminary Results and Future Perspectives |
title_sort | generator breast datamart—the novel breast cancer data discovery system for research and monitoring: preliminary results and future perspectives |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7911086/ https://www.ncbi.nlm.nih.gov/pubmed/33498985 http://dx.doi.org/10.3390/jpm11020065 |
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