Blood-Borne Biomarkers of Mortality Risk: Systematic Review of Cohort Studies, PLOS ONE, vol.339, issue.10, p.127550, 2015. ,
DOI : 10.1371/journal.pone.0127550.s003
A logic-based theory of deductive arguments??????This is an extended version of a paper entitled ???Towards a logic-based theory of argumentation??? published in the Proceedings of the National Conference on Artificial Intelligence (AAAI'2000), Austin, TX, MIT Press, Cambridge, MA, 2000., Artificial Intelligence, vol.128, issue.1-2, pp.203-235, 2001. ,
DOI : 10.1016/S0004-3702(01)00071-6
A review of current defeasible reasoning implementations, The Knowledge Engineering Review, vol.170, issue.03, pp.227-260, 2008. ,
DOI : 10.1007/s10458-005-1354-8
Building explainable artificial intelligence systems, In: AAAI. pp, pp.1766-1773, 2006. ,
DOI : 10.21236/ADA459166
Efficient argumentation for medical decision-making, p.KR, 2012. ,
Use of Framingham risk score and new biomarkers to predict cardiovascular mortality in older people: population based observational cohort study, BMJ, vol.338, issue.jan08 2, p.3083, 2009. ,
DOI : 10.1136/bmj.a3083
Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression, PLOS ONE, vol.arXiv, issue.6, p.148195, 2016. ,
DOI : 10.1371/journal.pone.0148195.s001
On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games, Artificial Intelligence, vol.77, issue.2, pp.321-358, 1995. ,
DOI : 10.1016/0004-3702(94)00041-X
Strong and weak forms of abstract argument defense. Computational Models of Argument: Proceedings of COMMA, p.216, 2008. ,
Argumentation in decision support for medical care planning for patients and clinicians, AAAI Spring Symposium: Argumentation for Consumers of Healthcare, pp.58-63, 2006. ,
Argumentation for Aggregating Clinical Evidence, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence, pp.361-368, 2010. ,
DOI : 10.1109/ICTAI.2010.59
Development and Validation of a Prognostic Index for 4-Year Mortality in Older Adults, JAMA, vol.295, issue.7, pp.801-808, 2006. ,
DOI : 10.1001/jama.295.7.801
, Heart disease and stroke statistics2009 update: a report from the american heart association statistics committee and stroke statistics subcommittee, pp.21-181, 2009.
Formalising Human Mental Workload as Non-monotonic Concept for Adaptive and Personalised Web-Design, International Conference on User Modeling, Adaptation, and Personalization, pp.369-373, 2012. ,
DOI : 10.1007/978-3-642-31454-4_38
A defeasible reasoning framework for human mental workload representation and assessment, Behaviour & Information Technology, vol.35, issue.2, pp.758-786, 2015. ,
DOI : 10.1016/S0019-9958(65)90241-X
Argumentation for Knowledge Representation, Conflict Resolution, Defeasible Inference and Its Integration with Machine Learning, Machine Learning for Health Informatics, pp.183-208, 2016. ,
DOI : 10.1007/978-3-319-28460-6_10
Defeasible Reasoning and Argument-Based Systems in Medical Fields: An Informal Overview, 2014 IEEE 27th International Symposium on Computer-Based Medical Systems, pp.376-381, 2014. ,
DOI : 10.1109/CBMS.2014.126
Argumentation theory for decision support in healthcare: a comparison with machine learning, International Conference on Brain and Health Informatics, pp.168-180, 2013. ,
Argumentation theory in health care, 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS), pp.1-6, 2012. ,
DOI : 10.1109/CBMS.2012.6266323
Combining statistics and arguments to compute trust, 9th International Conference on Autonomous Agents and Multiagent Systems, pp.209-216, 2010. ,
URL : https://hal.archives-ouvertes.fr/hal-00731959
Defeasible Reasoning, Cognitive Science, vol.13, issue.4, pp.481-518, 1987. ,
DOI : 10.1016/0004-3702(80)90014-4
An abstract framework for argumentation with structured arguments, Argument & Computation, vol.4, issue.2, pp.93-124, 2010. ,
DOI : 10.1017/CBO9780511802034
Bioinformatics advances for clinical biomarker development, Expert Opinion on Medical Diagnostics, vol.169, issue.8, pp.39-48, 2012. ,
DOI : 10.3109/00365513.2010.493420
Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile, pp.215-229, 2016. ,
DOI : 10.1007/978-3-319-12877-1
URL : https://hal.archives-ouvertes.fr/hal-01557636
Representing and inferring mental workload via defeasible reasoning: a comparison with the nasa task load index and the workload profile, 1st Workshop on Advances In Argumentation In Artificial Intelligence, pp.126-140, 2017. ,
Beyond data integration, Drug Discovery Today, vol.13, issue.13-14, pp.584-589, 2008. ,
DOI : 10.1016/j.drudis.2008.01.008
What are biomarkers?, Current Opinion in HIV and AIDS, vol.5, issue.6, p.463, 2010. ,
DOI : 10.1097/COH.0b013e32833ed177
Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology, OMICS: A Journal of Integrative Biology, vol.17, issue.12, pp.595-610, 2013. ,
DOI : 10.1089/omi.2013.0017