P08. 01 Building Personalized Follow-Up Care Through AI by Bringing the Lung Cancer Patient, Data Scientist and Oncologist Together

• Autoři: TORRENTE M.; FRANCO F.; CALVO V.; LORDUY A. Collazo; MENASALVAS E.; VIDAL M. E.; SOUSA P.; PIMENTAO J.; NOVÁČEK Vít; MINERVINI P.; FEY D.; COSTABELLO L.; POCS M.; PROVENCIO M.
• Rok publikování: 2021
• Druh: Článek v odborném periodiku
• Časopis / Zdroj: Journal of Thoracic Oncology
• Fakulta / Pracoviště MU: Fakulta informatiky
• www: https://www.jto.org/article/S1556-0864(21)02717-9/fulltext
• Doi: http://dx.doi.org/10.1016/j.jtho.2021.08.294
• Klíčová slova: machine learning; lung cancer; relapse; relapse prediction
• Popis: Survival rates of lung cancer patients were rather poor until recent decades, when screening protocols, diagnostic techniques improvement and novel therapeutic options were developed. This leads to a new challenge: to increase lung cancer patients’ post-treatment quality of life (QoL) and well-being. We here report on a first integration of an NLP framework for the analysis and integration of comprehensive eElectronic Health Records, genomic data, open data sources, wearable devices and QoL questionnaires, in order to determine the factors that predict poor health status and design personalized interventions that will improve the patient's QoL.