CARDIOCARE platform: A beyond the state of the art approach for the management of elderly multimorbid patients with breast cancer therapy induced cardiac toxicity

• Published in: 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) pp. 3907 - 3912
• Main Authors: Tsiouris, Kostas M., Karanasiou, Georgia, Sfakianakis, Stelios, Manikis, George, Kalliatakis, Grigoris, Antoniades, Athos, Lakkas, Lampros, Mauri, Davide, Mazzocco, Ketti, Papakonstantinou, Andri, Filippatos, Gerasimos, Constantinidou, Anastasia, Seruga, Bostjan, Conti, Constanza, Bucur, Anca, Pacella, Elsa, Marias, Kostas, Tsiknakis, Manolis, Fotiadis, Dimitrios I.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 05-12-2023
• Subjects: Breast cancer; cardiotoxicity; Machine learning; Medical treatment; mobile application; Mobile applications; risk stratification models; Technological innovation; Toxicology; Wearable computers
• ISSN: 2156-1133
• DOI: 10.1109/BIBM58861.2023.10385541

Breast cancer (BC) is the most common cancer in women in Europe and worldwide, with a high prevalence in middle-aged and older women. The last years, the evolution in the existing treatment approaches have contributed to improved clinical outcomes and survival rates. Nevertheless, BC therapy-related cardiotoxicity, poses a severe impact in the short- and long-term Quality of Life (QoL) and associated survival of the BC patients. This study demonstrates how the CARDIOCARE platform and the developed risk stratification models provides healthcare professionals with a valuable tool for effectively managing BC patients, preventing treatment induced cardiotoxicity and improving their QoL. This is accomplished through the integration of multi-source patient-specific data from patient-oriented mobile applications and wearable sensors, and by the employment of beyond the state-of-the-art data mining and machine learning approaches.