TY - GEN
T1 - An investigation of argumentation theory for the prediction of survival in elderly using biomarkers
AU - Rizzo, Lucas
AU - Majnaric, Ljiljana
AU - Dondio, Pierpaolo
AU - Longo, Luca
N1 - Publisher Copyright:
© IFIP International Federation for Information Processing 2018 Published by Springer International Publishing AG 2018. All Rights Reserved.
PY - 2018
Y1 - 2018
N2 - Research on the discovery, classification and validation of biological markers, or biomarkers, have grown extensively in the last decades. Newfound and correctly validated biomarkers have great potential as prognostic and diagnostic indicators, but present a complex relationship with pertinent endpoints such as survival or other diseases manifestations. This research proposes the use of computational argumentation theory as a starting point for the resolution of this problem for cases in which a large amount of data is unavailable. A knowledge-base containing 51 different biomarkers and their association with mortality risks in elderly was provided by a clinician. It was applied for the construction of several argument-based models capable of inferring survival or not. The prediction accuracy and sensitivity of these models were investigated, showing how these are in line with inductive classification using decision trees with limited data.
AB - Research on the discovery, classification and validation of biological markers, or biomarkers, have grown extensively in the last decades. Newfound and correctly validated biomarkers have great potential as prognostic and diagnostic indicators, but present a complex relationship with pertinent endpoints such as survival or other diseases manifestations. This research proposes the use of computational argumentation theory as a starting point for the resolution of this problem for cases in which a large amount of data is unavailable. A knowledge-base containing 51 different biomarkers and their association with mortality risks in elderly was provided by a clinician. It was applied for the construction of several argument-based models capable of inferring survival or not. The prediction accuracy and sensitivity of these models were investigated, showing how these are in line with inductive classification using decision trees with limited data.
KW - Argumentation theory
KW - Biomarkers
KW - Defeasible reasoning
UR - http://www.scopus.com/inward/record.url?scp=85049555459&partnerID=8YFLogxK
UR - https://arrow.tudublin.ie/scschcomcon/221/
U2 - 10.1007/978-3-319-92007-8_33
DO - 10.1007/978-3-319-92007-8_33
M3 - Conference contribution
AN - SCOPUS:85049555459
SN - 9783319920061
T3 - IFIP Advances in Information and Communication Technology
SP - 385
EP - 397
BT - Artificial Intelligence Applications and Innovations - 14th IFIP WG 12.5 International Conference, AIAI 2018, Proceedings
A2 - Iliadis, Lazaros
A2 - Plagianakos, Vassilis
A2 - Maglogiannis, Ilias
PB - Springer New York LLC
T2 - 14th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2018
Y2 - 25 May 2018 through 27 May 2018
ER -