| TORRENTE, M., F. FRANCO, V. CALVO, A. Collazo LORDUY, E. MENASALVAS, M. E. VIDAL, P. SOUSA, J. PIMENTAO, Vít NOVÁČEK, P. MINERVINI, D. FEY, L. COSTABELLO, M. POCS and M. PROVENCIO. P08. 01 Building Personalized Follow-Up Care Through AI by Bringing the Lung Cancer Patient, Data Scientist and Oncologist Together. Journal of Thoracic Oncology. Elsevier, 2021, vol. 16, No 10, p. 991-992. ISSN 1556-1380. Available from: https://dx.doi.org/10.1016/j.jtho.2021.08.294. |
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@article{1848074,
author = {Torrente, M. and Franco, F. and Calvo, V. and Lorduy, A. Collazo and Menasalvas, E. and Vidal, M. E. and Sousa, P. and Pimentao, J. and Nováček, Vít and Minervini, P. and Fey, D. and Costabello, L. and Pocs, M. and Provencio, M.},
article_number = {10},
doi = {http://dx.doi.org/10.1016/j.jtho.2021.08.294},
keywords = {machine learning; lung cancer; relapse; relapse prediction},
language = {eng},
issn = {1556-1380},
journal = {Journal of Thoracic Oncology},
title = {P08. 01 Building Personalized Follow-Up Care Through AI by Bringing the Lung Cancer Patient, Data Scientist and Oncologist Together},
url = {https://www.jto.org/article/S1556-0864(21)02717-9/fulltext},
volume = {16},
year = {2021}
}
TY - JOUR
ID - 1848074
AU - 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.
PY - 2021
TI - P08. 01 Building Personalized Follow-Up Care Through AI by Bringing the Lung Cancer Patient, Data Scientist and Oncologist Together
JF - Journal of Thoracic Oncology
VL - 16
IS - 10
SP - 991-992
EP - 991-992
PB - Elsevier
SN - 15561380
KW - machine learning
KW - lung cancer
KW - relapse
KW - relapse prediction
UR - https://www.jto.org/article/S1556-0864(21)02717-9/fulltext
N2 - 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.
ER -
TORRENTE, M., F. FRANCO, V. CALVO, A. Collazo LORDUY, E. MENASALVAS, M. E. VIDAL, P. SOUSA, J. PIMENTAO, Vít NOVÁČEK, P. MINERVINI, D. FEY, L. COSTABELLO, M. POCS and M. PROVENCIO. P08. 01 Building Personalized Follow-Up Care Through AI by Bringing the Lung Cancer Patient, Data Scientist and Oncologist Together. \textit{Journal of Thoracic Oncology}. Elsevier, 2021, vol.~16, No~10, p.~991-992. ISSN~1556-1380. Available from: https://dx.doi.org/10.1016/j.jtho.2021.08.294.
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