Sensor data analysis and development of machine learning models for detection of glaucoma

Hubert Świerczyński; Juliusz Pukacki; Szymon Szczęsny; Cezary Mazurek; Robert Wasilewicz

doi:10.1016/j.bspc.2023.105350

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Title

Sensor data analysis and development of machine learning models for detection of glaucoma

Authors

Hubert Świerczyński (WIiT) ^{[ 1 ][ 2.3 ][ SzD ]}
Juliusz Pukacki
Szymon Szczęsny (WIiT) ^{[ 2 ][ 2.3 ][ P ]}
Cezary Mazurek
Robert Wasilewicz

^{[ 1 ]} Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | ^{[ 2 ]} Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | ^{[ SzD ]} doctoral school student | ^{[ P ]} employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2023

Published in

Biomedical Signal Processing and Control

Journal year: 2023 | Journal volume: vol. 86, part C

Article type

scientific article

Publication language

english

Keywords

EN

Machine learning
Glaucoma
Personalized medicine
Sensors
Time series

Abstract

EN This paper focuses on analysis of data acquired using Triggerfish contact lens sensor and devices for continuous monitoring of cardiovascular system properties. One of the aims of our research is to build machine learning models that can be applied in clinical practice to detect glaucoma independently of currently used imaging techniques. We show that cardiac sensor data derived attributes are complementary to Triggerfish data and improve mean AUC estimates of the predictive models. We propose methods of attribute generation for raw data recorded by the devices. During data preprocessing we consider division of 24-hour monitoring period for time intervals depending on physiological circadian cycle properties. Comprehensive comparison of model predictive performance metrics is included. Our predictive model involving measurements of corneal biomechanical properties and sensor data based attributes provides AUC of 0.87. It can support glaucoma detection without direct intraocular pressure measurement. We also refer to the issues related to personalized medicine and application of machine learning techniques.

Date of online publication

18.08.2023

Pages (from - to)

105350-1 - 105350-9

DOI

10.1016/j.bspc.2023.105350

URL

https://www.sciencedirect.com/science/article/pii/S1746809423007838?via%3Dihub

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Article Number: 105350

Ministry points / journal

140