Supporting patients and clinicians during the breast cancer care path with AI : The Arianna solution

Copyright © 2023 Elsevier B.V. All rights reserved..

The onset of cancer disease is a traumatic experience for both patients and their families that suddenly change the patient's life and is accompanied by important physical, emotional, and psycho-social problems. The complexity of this scenario has been exacerbated by the COVID-19 pandemic which dramatically affected the continuity of the provision of optimal care to chronic patients. Telemedicine can support the management of oncology care paths by furnishing a suite of effective and efficient tools to monitor the therapies of cancer patients. In particular, this is a suitable setting for therapies that are administered at home. In this paper, we present an AI-based system, called Arianna, designed and implemented to support and monitor patients treated by the professionals belonging to the Breast Cancer Unit Network (BCU-Net) along the entire clinical path of breast cancer treatment. We describe in this work the three modules composing the Arianna system (the tools for patients and clinicians, and the symbolic AI-based module). The system has been validated in a qualitative way and we demonstrated how the Arianna solution reached a high level of acceptability by all types of end-users by making it suitable for a concrete integration into the daily practice of the BCU-Net.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:138

Enthalten in:

Artificial intelligence in medicine - 138(2023) vom: 27. Apr., Seite 102514

Sprache:

Englisch

Beteiligte Personen:

Dragoni, Mauro [VerfasserIn]
Eccher, Claudio [VerfasserIn]
Ferro, Antonella [VerfasserIn]
Bailoni, Tania [VerfasserIn]
Maimone, Rosa [VerfasserIn]
Zorzi, Andrea [VerfasserIn]
Bacchiega, Alessandro [VerfasserIn]
Stulzer, Gabriele [VerfasserIn]
Ghidini, Chiara [VerfasserIn]

Links:

Volltext

Themen:

Artificial intelligence
Breast cancer
Business process model
Journal Article
Knowledge management
Patients care paths
Reasoning

Anmerkungen:

Date Completed 31.03.2023

Date Revised 05.04.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.artmed.2023.102514

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM354955357