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A hybrid artificial intelligence solution approach to aftercare for cancer patients
1
Zitationen
21
Autoren
2023
Jahr
Abstract
Abstract This publication presents a solution approach to oncological aftercare for cancer patients by means of artificial intelligence (AI) methods. This approach shall support patients in overcoming the after-effects of therapy effectively with suitable supportive actions and health-care professionals in goal-oriented planning of these actions. Different AI methods are used for analyzing patients’ needs for supportive actions depending on the available health data and for a monitoring of these actions. Decision support methods are used for effective planning of actions based on the AI results of analysis. The solution approach is realized in the form of a web application for health-care professionals, which allows for data analysis and planning of actions, and a mobile application for patients, which facilitates documentation and monitoring of supportive actions. In combination, they facilitate a closed-loop workflow for the effective cooperation of health-care professionals and cancer patients. The solution approach is illustrated for an exemplary case scenario of colorectal cancer.
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Autoren
- Alexander Scherrer
- Tobias J. Zimmermann
- Sinan Riedel
- Stefanos Venios
- Sotirios Koussouris
- Maria Plakia
- Sotiris Diamantopoulos
- S. Athanassopoulos
- Paris Emmanouil Laras
- Fihmi Mousa
- Robert Zifrid
- H. Tillil
- Isa Wasswa Musisi
- Thanos Kosmidis
- Joaquim C. Reis
- Markus Moehler
- Gabrielle Oestreicher
- Ilias Kalamaras
- Konstantina Pantelidou
- Konstantinos Votis
- Charalampos Vassiliou
Institutionen
- Fraunhofer Institute for Industrial Mathematics(DE)
- EXUS (United Kingdom)(GB)
- King's College Hospital(GB)
- University of Lisbon(PT)
- Johannes Gutenberg University Mainz(DE)
- University Medical Center of the Johannes Gutenberg University Mainz(DE)
- Centre for Research and Technology Hellas(GR)
- Algosystems (Greece)(GR)