Descrizione del progetto
Analisi dei dati per migliorare la qualità della vita dei sopravvissuti al cancro
Negli ultimi anni, il numero di sopravvissuti al cancro è aumentato grazie ai progressi nella diagnosi e nel trattamento. Garantire la qualità della vita post-trattamento dei sopravvissuti rimane una sfida. Il progetto CLARIFY, finanziato dall’UE, identificherà i fattori di rischio per il deterioramento in un paziente al termine del trattamento oncologico. In particolare, raccoglierà dati sui sopravvissuti da carcinoma mammario, polmonare e linfoma (i tipi più diffusi) da alcuni ospedali in Spagna. Utilizzando megadati e tecniche di intelligenza artificiale, integrerà tutti i dati con le informazioni biomediche pertinenti pubblicamente disponibili, nonché con le informazioni dei dispositivi indossabili utilizzati dopo il trattamento. I dati saranno analizzati in modo da prevedere il rischio paziente-specifico di sviluppare effetti secondari e tossicità provenienti dai trattamenti contro il cancro.
Obiettivo
There were 17 million new cases of cancer diagnosed worldwide in 2018. Survival rates of cancer patients were rather poor until recent decades, when diagnostic techniques have been improved and novel therapeutic options have been developed. It is estimated that more than 50% of adult patients diagnosed with cancer live at least 5 years in the US and Europe. This situation leads to a new challenge: to increase the cancer patients’ post-treatment quality of life and well-being. This proposal aims at identifying cancer survivors from three prevalent types of cancer, including breast, lung and lymphomas. The patient data will be collected from different Spanish hospitals and the selection will be based on ongoing health and supportive care needs of the particular patient types. We will determine the personalised factors that predict poor health status after specific oncological treatments. For this aim, Big Data and Artificial Intelligence techniques will be used to integrate all available patient´s information with publicly available relevant biomedical databases as well as information from wearable devices used after the treatment. To predict patient-specific risk of developing secondary effects and toxicities of their cancer treatments, we will build novel models based on statistical relational learning and explainable AI techniques on top of the integrated knowledge graphs. The models will utilise background knowledge of the associated cancer biology and thus will help clinicians to make evidence-based post-treatment decisions in a way that is not possible at all with any existing approach. In summary, CLARIFY proposes to integrate and analyse large volumes of heterogenous multivariate data to facilitate early discovery of risk factors that may deteriorate a patient condition after the end of oncological treatment. This will effectively help to stratify cancer survivors by risk in order to personalize their follow-up by better assessment of their needs.
Campo scientifico
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencescomputer and information sciencesinternetinternet of things
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencescomputer and information sciencesknowledge engineering
- medical and health sciencesclinical medicineoncology
Parole chiave
Programma(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-SC1-DTH-2019
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
28046 MADRID
Spagna