ASCAPE (Artificial intelligence Supporting CAncer Patients across Europe) is a collaborative research project involving 15 partners from 7 countries, including academic medical centers, SMEs (small and medium-sized enterprises), research centers and universities, aiming to leverage the recent advances in Big Data and AI (Artificial Intelligence) to support cancer patients' Quality of Life (QoL) and health status. Specifically, ASCAPE aims to provide personalized- and AI-based predictions for QoL issues in breast- and prostate cancer patients as well as suggest potential interventions to their physicians. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 875351.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
500
Follow-up through ASCAPE platform including AI-based predictions for health-related QoL issues and suggestions for personalized interventions depending on the type of QoL issue that needs to be tackled. The ASCAPE-based follow-up strategy includes follow-up through validated QoL questionnaires, wearables for capturing active monitoring data, and mobile apps for answering the questionnaires and capturing potential health-related issues.
Urology Department, Sismanogleio General Hospital
Athens, Greece
Oncology Department, Hospital Clínic de Barcelona
Barcelona, Spain
Department of Oncology, Örebro University Hospital
Örebro, Sweden
Department of Oncology, University Hospital of Uppsala
Uppsala, Sweden
CareAcross
London, United Kingdom
Patients' experience using ASCAPE-based follow-up
Patients' experience to be followed with the help of an AI-based system per se, patients' satisfaction with this type of follow-up, potential barriers and facilitators of using wearables during follow-up, and motivation for following interventions based on AI-based follow-up
Time frame: At the end of intervention (month 12)
Patients' engagement to ASCAPE-based follow-up
Number of questionnaires submitted per patients; total time that the patients used the wearables
Time frame: Every three months until the end of intervention (12 months)
Patients' adherence to AI-based proposed intervention
Time frame: Every three months until the end of intervention (12 months)
Assessment of health-related QoL over time
Time frame: Every three months until the end of intervention (12 months)
Physicians' views and experience regarding ASCAPE-based follow-up in terms of implementation into clinical practice
The following aspects will be considered: improvement in patient-doctor relationship; AI-based follow-up's efficiency to capture relevant QoL issues on time; changes in management or referrals made due to AI-based predictions; usefulness of the information provided by AI-based models; acceptability of integrating AI-based follow-up into clinical practice; assessment of the time needed to use AI-based follow-up in clinical practice
Time frame: At the end of intervention (month 12)
Physicians' views and experience regarding ASCAPE-based follow-up in terms of interaction
This outcome includes issues related to the interaction between the AI-based follow-up platform and physicians as usability, accessibility, and qualitative assessment of the interface.
Time frame: At the end of intervention (month 12)
Physicians' experience in using ASCAPE-based follow-up
This outcome includes issues related to trustworthiness, how confident physicians are regarding the reliability of AI-based follow-up, and psychological aspects in using an AI-based platform in clinical practice as perceived substitution crisis and behavioural intention.
Time frame: At the end of intervention (month 12)
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