Optimization of a Sequential Decision Making Problem for a Rare Disease Diagnostic Application

Rémi Besson, Erwan Pennec, Erwan Pennec, Emmanuel Spaggiari, Antoine Neuraz, Julien Stirnemann, Stéphanie Allassonnière

2020

Abstract

In this work, we propose a new optimization formulation for a sequential decision making problem for a rare disease diagnostic application. We aim to minimize the number of medical tests necessary to achieve a state where the uncertainty regarding the patient’s disease is less than a predetermined threshold. In doing so, we take into account the need in many medical applications, to avoid as much as possible, any misdiagnosis. To solve this optimization task, we investigate several reinforcement learning algorithms and make them operable in our high-dimensional setting: the strategies learned are much more efficient than classical greedy strategies.

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Paper Citation


in Harvard Style

Besson R., Pennec E., Spaggiari E., Neuraz A., Stirnemann J. and Allassonnière S. (2020). Optimization of a Sequential Decision Making Problem for a Rare Disease Diagnostic Application. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-395-7, pages 475-482. DOI: 10.5220/0008938804750482


in Bibtex Style

@conference{icaart20,
author={Rémi Besson and Erwan Pennec and Emmanuel Spaggiari and Antoine Neuraz and Julien Stirnemann and Stéphanie Allassonnière},
title={Optimization of a Sequential Decision Making Problem for a Rare Disease Diagnostic Application},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2020},
pages={475-482},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008938804750482},
isbn={978-989-758-395-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Optimization of a Sequential Decision Making Problem for a Rare Disease Diagnostic Application
SN - 978-989-758-395-7
AU - Besson R.
AU - Pennec E.
AU - Spaggiari E.
AU - Neuraz A.
AU - Stirnemann J.
AU - Allassonnière S.
PY - 2020
SP - 475
EP - 482
DO - 10.5220/0008938804750482