Interactive Lungs Auscultation with Reinforcement Learning Agent

Tomasz Grzywalski, Riccardo Belluzzo, Szymon Drgas, Agnieszka Cwalińska, Honorata Hafke-Dys

2019

Abstract

To perform a precise auscultation for the purposes of examination of respiratory system normally requires the presence of an experienced doctor. With most recent advances in machine learning and artificial intelligence, automatic detection of pathological breath phenomena in sounds recorded with stethoscope becomes a reality. But to perform a full auscultation in home environment by layman is another matter, especially if the patient is a child. In this paper we propose a unique application of Reinforcement Learning for training an agent that interactively guides the end user throughout the auscultation procedure. We show that intelligent selection of auscultation points by the agent reduces time of the examination fourfold without significant decrease in diagnosis accuracy compared to exhaustive auscultation.

Paper Citation

in Harvard Style

Grzywalski T., Belluzzo R., Drgas S., Cwalińska A. and Hafke-Dys H. (2019). Interactive Lungs Auscultation with Reinforcement Learning Agent.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 824-832. DOI: 10.5220/0007573608240832

in Bibtex Style

@conference{icaart19,
author={Tomasz Grzywalski and Riccardo Belluzzo and Szymon Drgas and Agnieszka Cwalińska and Honorata Hafke-Dys},
title={Interactive Lungs Auscultation with Reinforcement Learning Agent},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={824-832},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007573608240832},
isbn={978-989-758-350-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Interactive Lungs Auscultation with Reinforcement Learning Agent
SN - 978-989-758-350-6
AU - Grzywalski T.
AU - Belluzzo R.
AU - Drgas S.
AU - Cwalińska A.
AU - Hafke-Dys H.
PY - 2019
SP - 824
EP - 832
DO - 10.5220/0007573608240832