Artificial intelligence supporting cancer patients across Europe-The ASCAPE project.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2022
2022
Historique:
received:
08
02
2022
accepted:
11
02
2022
entrez:
21
4
2022
pubmed:
22
4
2022
medline:
26
4
2022
Statut:
epublish
Résumé
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. 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. 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 on clinicaltrials.gov: NCT04879563.
Identifiants
pubmed: 35446854
doi: 10.1371/journal.pone.0265127
pii: PONE-D-22-02528
pmc: PMC9022843
doi:
Banques de données
ClinicalTrials.gov
['NCT04879563']
Types de publication
Clinical Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0265127Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
Arch Intern Med. 2006 May 22;166(10):1092-7
pubmed: 16717171
Ann Oncol. 2013 Aug;24(8):2151-8
pubmed: 23567145
N Engl J Med. 2008 Mar 20;358(12):1250-61
pubmed: 18354103
Ann Oncol. 2020 Sep;31(9):1119-1134
pubmed: 32593798
BJU Int. 2016 Jun;117(6B):E10-9
pubmed: 25818406
CA Cancer J Clin. 2019 Sep;69(5):363-385
pubmed: 31184787
J Biomed Inform. 2016 Apr;60:224-33
pubmed: 26911524
Eur J Oncol Nurs. 2015 Aug;19(4):405-18
pubmed: 25613370
JCO Clin Cancer Inform. 2020 Sep;4:799-810
pubmed: 32926637
Eur Urol. 2017 Apr;71(4):618-629
pubmed: 27568654
Ann Oncol. 2019 Aug 1;30(8):1194-1220
pubmed: 31161190
JAMA Netw Open. 2020 Mar 2;3(3):e200506
pubmed: 32142127
Int Health. 2020 Jul 1;12(4):241-245
pubmed: 32300794
Front Oncol. 2020 Jun 16;10:864
pubmed: 32612947
Rehabil Oncol. 2016 Jan;34(1):27-35
pubmed: 27134804
Rehabil Oncol. 2017 Jul;35(3):137-143
pubmed: 29082117
Urology. 1997 Jun;49(6):822-30
pubmed: 9187685
J Gen Intern Med. 2001 Sep;16(9):606-13
pubmed: 11556941