Artificial intelligence supporting cancer patients across Europe - The ASCAPE projectShow others and affiliations
2022 (English)In: PLOS ONE, E-ISSN 1932-6203, Vol. 17, no 4, article id e0265127Article in journal (Refereed) Published
Abstract [en]
INTRODUCTION: Breast and prostate cancer survivors can experience impaired quality of life (QoL) in several QoL domains. The current strategy to support cancer survivors with impaired QoL is suboptimal, leading to unmet patient needs. ASCAPE aims to provide personalized- and artificial intelligence (AI)-based predictions for QoL issues in breast- and prostate cancer patients as well as to suggest potential interventions to their physicians to offer a more modern and holistic approach on cancer rehabilitation.
METHODS AND ANALYSES: An AI-based platform aiming to predict QoL issues and suggest appropriate interventions to clinicians will be built based on patient data gathered through medical records, questionnaires, apps, and wearables. This platform will be prospectively evaluated through a longitudinal study where breast and prostate cancer survivors from four different study sites across the Europe will be enrolled. The evaluation of the AI-based follow-up strategy through the ASCAPE platform will be based on patients' experience, engagement, and potential improvement in QoL during the study as well as on clinicians' view on how ASCAPE platform impacts their clinical practice and doctor-patient relationship, and their experience in using the platform.
ETHICS AND DISSEMINATION: ASCAPE is the first research project that will prospectively investigate an AI-based approach for an individualized follow-up strategy for patients with breast- or prostate cancer focusing on patients' QoL issues. ASCAPE represents a paradigm shift both in terms of a more individualized approach for follow-up based on QoL issues, which is an unmet need for cancer survivors, and in terms of how to use Big Data in cancer care through democratizing the knowledge and the access to AI and Big Data related innovations.
TRIAL REGISTRATION: Trial Registration on clinicaltrials.gov: NCT04879563.
Place, publisher, year, edition, pages
Public Library of Science , 2022. Vol. 17, no 4, article id e0265127
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:oru:diva-98665DOI: 10.1371/journal.pone.0265127ISI: 000795468200033PubMedID: 35446854Scopus ID: 2-s2.0-85128651685OAI: oai:DiVA.org:oru-98665DiVA, id: diva2:1653474
2022-04-222022-04-222022-06-07Bibliographically approved