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Patients-centered survivorship care plan after Cancer treatments based on Big Data and AI

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The main challenge of PERSIST is to improve the quality of life of breast and colorectal cancer survivors. Using artificial intelligence and Big Data technologies, experts will develop an innovative ecosystem to support the decision-making of physicians contributing to optimal treatment decisions.

The complete PERSIST system will incorporate a clinical decision support system based on new models of health data analysis; and a mHealth system for remote and personalized monitoring of each patient. In addition, the partners will develop a Big Data platform that integrates the two previous systems and will be connected to the clinical history systems of any hospital.

The initiative includes a transnational pilot with more than 150 patients and 32 health professionals from 4 different countries, which will be decisive to establish a co-creation methodology that will cover the initial phases of the project until its conclusion.

Dissemination

  • Calbimonte, J.-P. (2023). Patient Trajectory Analysis for Cancer Survivorship. Talk Presented at the Foire du Valais 2023.

Publications

  • Smrke, U., Abalde-Cela, S., Loly, C., Calbimonte, J.-P., Pires, L. R., Lin, S., Sánchez, A., Tement, S. & Mlakar, I. (2024). Quality of Life of Colorectal Cancer Survivors: Mapping the Key Indicators by Expert Consensus and Measures for Their Assessment. Healthcare, 12(12). https://doi.org/10.3390/healthcare12121235
  • Manzo, G., Pannatier, Y., Duflot, P., Kolh, P., Chavez, M., Bleret, V., Calvaresi, D., Jimenez del Toro, O., Schumacher, M. & Calbimonte, J.-P. (2023). Breast cancer survival analysis agents for clinical decision support. Computer Methods and Programs in Biomedicine, 231, 107373. https://doi.org/https://doi.org/10.1016/j.cmpb.2023.107373
  • Manzo, G., Calvaresi, D., Jimenez-del-Toro, O., Calbimonte, J.-P. & Schumacher, M. (2021). Cohort and Trajectory Analysis in Multi-Agent Support Systems for Cancer Survivors. Journal of Medical Systems, 45(12). https://doi.org/10.1007/s10916-021-01770-3
  • Calbimonte, J.-P., Calvaresi, D. & Schumacher, M. (2020). Decentralized Management of Patient Profiles and Trajectories through Semantic Web Agents. Proc. Of the Third International Workshop on Semantic Web Meets Health Data Management (SWH 2020) Co-Located with the 19th International Semantic Web Conference (ISWC 2020), Vol-2759, 19–29. http://ceur-ws.org/Vol-2759/paper2.pdf
  • Calvaresi, D., Schumacher, M. & Calbimonte, J.-P. (2020). Agent-based Modeling for Ontology-driven Analysis of Patient Trajectories. Journal of Medical Systems, 44, 158. https://doi.org/https://doi.org/10.1007/s10916-020-01620-8