A hybrid artificial intelligence solution approach to aftercare for cancer patients
Article Ecrit par: Scherrer, Alexander ; Zimmermann, Tobias ; Riedel, Sinan ; Venios, Stefanos ; Koussouris, Sotiris ; Plakia, Maria ; Diamantopoulos, Sotiris ; Athanassopoulos, Sotiris ; Laras, Paris ; Mousa, Fihmi ; Zifrid, Robert ; Tillil, Hartmut ; Musisi, Isa Wasswa ; Kosmidis, Thanos ; Reis, Joaquim C. ; Moehler, Markus ; Oestreicher, Gabrielle ; Kalamaras, Ilias ; Pantelidou, Konstantina ; Votis, Konstantinos ; Vassiliou, Charalampos ;
Résumé: 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.
Langue:
Anglais